BibSLEIGH — probability tag

probability

probability

Tag #probability

1900 papers:

POPL-2020-BartheHL #logic: A probabilistic separation logic (GB, JH, KL), p. 30.
POPL-2020-DahlqvistK #higher-order #semantics #source code: Semantics of higher-order probabilistic programs with conditioning (FD, DK), p. 29.
POPL-2020-HarkKGK #bound #induction #verification: Aiming low is harder: induction for lower bounds in probabilistic program verification (MH, BLK, JG, JPK), p. 28.
POPL-2020-LeeYRY #source code #towards: Towards verified stochastic variational inference for probabilistic programs (WL0, HY, XR, HY), p. 33.
POPL-2020-LewCSCM #programmable #semantics: Trace types and denotational semantics for sound programmable inference in probabilistic languages (AKL, MFCT, BS, MC, VKM), p. 32.
POPL-2020-SaadFRM #approximate: Optimal approximate sampling from discrete probability distributions (FAS, CEF, MCR, VKM), p. 31.
POPL-2020-VandenbrouckeS #functional #named: PλωNK: functional probabilistic NetKAT (AV, TS), p. 27.
POPL-2020-WangFCDX #proving #random #source code #termination: Proving expected sensitivity of probabilistic programs with randomized variable-dependent termination time (PW, HF0, KC, YD, MX), p. 30.
EDM-2019-BanjadeR #logic #student #tutorial #using: Assessing Student Response in Tutorial Dialogue Context using Probabilistic Soft Logic (RB, VR).
EDM-2019-SunahaseBK #assessment #modelling: Probabilistic Modeling of Peer Correction and Peer Assessment (TS, YB, HK).
ICSME-2019-Alqadi #complexity #fault: The Relationship Between Cognitive Complexity and the Probability of Defects (BSA), pp. 600–604.
FM-2019-CeskaHJK #sketching #synthesis: Counterexample-Driven Synthesis for Probabilistic Program Sketches (MC0, CH, SJ, JPK), pp. 101–120.
FM-2019-KwiatkowskaN0S #concurrent #game studies #model checking: Equilibria-Based Probabilistic Model Checking for Concurrent Stochastic Games (MK, GN, DP0, GS), pp. 298–315.
FSCD-2019-Ehrhard: Differentials and Distances in Probabilistic Coherence Spaces (TE), p. 17.
FSCD-2019-Faggian #normalisation #termination: Probabilistic Rewriting: Normalization, Termination, and Unique Normal Forms (CF), p. 25.
FSCD-2019-Horne #linear #logic #proving: The Sub-Additives: A Proof Theory for Probabilistic Choice extending Linear Logic (RH), p. 16.
FSCD-2019-KasterovicP #call-by #lazy evaluation #power of #λ-calculus: The Discriminating Power of the Let-In Operator in the Lazy Call-by-Name Probabilistic lambda-Calculus (SK, MP), p. 20.
FSCD-2019-LagoL #on the #λ-calculus: On the Taylor Expansion of Probabilistic lambda-terms (UDL, TL), p. 16.
FSCD-2019-Yang #programming language #semantics: Some Semantic Issues in Probabilistic Programming Languages (Invited Talk) (HY), p. 6.
IFM-2019-DubslaffKT #model checking: Ontology-Mediated Probabilistic Model Checking (CD, PK, AYT), pp. 194–211.
IFM-2019-LanotteT #automaton #metric #similarity: Computing Bisimilarity Metrics for Probabilistic Timed Automata (RL, ST), pp. 303–321.
IFM-2019-LoharPD #analysis #fault: Sound Probabilistic Numerical Error Analysis (DL, MP, ED), pp. 322–340.
CoG-2019-BonomettiRHWD #estimation #interactive #modelling: Modelling Early User-Game Interactions for Joint Estimation of Survival Time and Churn Probability (VB, CR, MH, ARW, AD), pp. 1–8.
CoG-2019-PellingG #behaviour: Two Human-Like Imitation-Learning Bots with Probabilistic Behaviors (CP, HJG), pp. 1–7.
FDG-2019-GandhiH #generative #modelling #using #visual notation: Guided open story generation using probabilistic graphical models (SG, BH), p. 7.
CIKM-2019-BremenDJ #logic programming #query: Ontology-Mediated Queries over Probabilistic Data via Probabilistic Logic Programming (TvB, AD, JCJ), pp. 2437–2440.
CIKM-2019-GaoLY #fine-grained: Fine-Grained Geolocalization of User-Generated Short Text based on Weight Probability Model (CG, YL, JY), pp. 2089–2092.
CIKM-2019-MiloMY #analysis #datalog #named: PODIUM: Probabilistic Datalog Analysis via Contribution Maximization (TM, YM, BY), pp. 2865–2868.
CIKM-2019-RoiteroBUM #simulation #towards: Towards Stochastic Simulations of Relevance Profiles (KR, AB, JU, SM), pp. 2217–2220.
ECIR-p1-2019-FerranteFL #crowdsourcing: Stochastic Relevance for Crowdsourcing (MF, NF0, EL), pp. 755–762.
ECIR-p1-2019-LandinVPB #modelling #named #recommendation: PRIN: A Probabilistic Recommender with Item Priors and Neural Models (AL, DV, JP, ÁB), pp. 133–147.
ICML-2019-AkimotoSYUSN #adaptation #architecture: Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search (YA, SS, NY, KU, SS, KN), pp. 171–180.
ICML-2019-AssranLBR #distributed #learning: Stochastic Gradient Push for Distributed Deep Learning (MA, NL, NB, MR), pp. 344–353.
ICML-2019-AydoreTV: Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data (SA, BT, GV), pp. 385–394.
ICML-2019-BehpourLZ #learning #predict: Active Learning for Probabilistic Structured Prediction of Cuts and Matchings (SB, AL, BDZ), pp. 563–572.
ICML-2019-BiePC #network: Stochastic Deep Networks (GdB, GP, MC), pp. 1556–1565.
ICML-2019-CanGZ #convergence #linear: Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances (BC, MG, LZ), pp. 891–901.
ICML-2019-ChaudhuriK #identification #multi: PAC Identification of Many Good Arms in Stochastic Multi-Armed Bandits (ARC, SK), pp. 991–1000.
ICML-2019-ChuBG #functional #learning: Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning (CC, JHB, PWG), pp. 1213–1222.
ICML-2019-DeneviCGP: Learning-to-Learn Stochastic Gradient Descent with Biased Regularization (GD, CC, RG, MP), pp. 1566–1575.
ICML-2019-DiakonikolasKK0 #named #optimisation #robust: Sever: A Robust Meta-Algorithm for Stochastic Optimization (ID, GK0, DK, JL0, JS, AS), pp. 1596–1606.
ICML-2019-DunckerBBS #learning #modelling: Learning interpretable continuous-time models of latent stochastic dynamical systems (LD, GB, JB, MS), pp. 1726–1734.
ICML-2019-EichnerKMST: Semi-Cyclic Stochastic Gradient Descent (HE, TK, BM, NS, KT), pp. 1764–1773.
ICML-2019-HuangCH #multi #optimisation #performance: Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization (FH, SC, HH), pp. 2839–2848.
ICML-2019-KasaiJM #adaptation #algorithm #matrix: Riemannian adaptive stochastic gradient algorithms on matrix manifolds (HK, PJ, BM), pp. 3262–3271.
ICML-2019-KoloskovaSJ #algorithm #communication #distributed #optimisation: Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication (AK, SUS, MJ), pp. 3478–3487.
ICML-2019-KoolHW #sequence: Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement (WK, HvH, MW), pp. 3499–3508.
ICML-2019-KulunchakovM #optimisation #sequence: Estimate Sequences for Variance-Reduced Stochastic Composite Optimization (AK, JM), pp. 3541–3550.
ICML-2019-LiuRTJM: Rao-Blackwellized Stochastic Gradients for Discrete Distributions (RL, JR, NT, MIJ, JDM), pp. 4023–4031.
ICML-2019-LiuS19a: Data Poisoning Attacks on Stochastic Bandits (FL0, NBS), pp. 4042–4050.
ICML-2019-MaoFRAFW #estimation #graph #order: A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs (JM, JNF, TR, MAS, GF, SW), pp. 4343–4351.
ICML-2019-MehtaCR #graph #network: Stochastic Blockmodels meet Graph Neural Networks (NM, LC, PR), pp. 4466–4474.
ICML-2019-MetelT #optimisation: Simple Stochastic Gradient Methods for Non-Smooth Non-Convex Regularized Optimization (MRM, AT), pp. 4537–4545.
ICML-2019-ParkSLS #empirical #network: The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study (DSP, JSD, QVL, SLS), pp. 5042–5051.
ICML-2019-RakellyZFLQ #learning #performance: Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables (KR, AZ, CF, SL, DQ), pp. 5331–5340.
ICML-2019-RollandKISC #learning #performance #testing: Efficient learning of smooth probability functions from Bernoulli tests with guarantees (PR, AK, AI, AS, VC), pp. 5459–5467.
ICML-2019-SimsekliSG #analysis #network: A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks (US, LS, MG), pp. 5827–5837.
ICML-2019-StelznerPK #modelling #performance: Faster Attend-Infer-Repeat with Tractable Probabilistic Models (KS, RP, KK), pp. 5966–5975.
ICML-2019-TaghvaeiM: Accelerated Flow for Probability Distributions (AT, PGM), pp. 6076–6085.
ICML-2019-TangYLZL #named #parallel: DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-pass Error-Compensated Compression (HT, CY, XL, TZ, JL0), pp. 6155–6165.
ICML-2019-VedantamDLRBP #modelling #visual notation: Probabilistic Neural Symbolic Models for Interpretable Visual Question Answering (RV, KD, SL, MR, DB, DP), pp. 6428–6437.
ICML-2019-WengCNSBOD #approach #named #network #robust #verification: PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach (LW, PYC, LMN, MSS, AB, IVO, LD), pp. 6727–6736.
ICML-2019-WilkinsonARSS #analysis: End-to-End Probabilistic Inference for Nonstationary Audio Analysis (WJW, MRA, JDR, DS, AS), pp. 6776–6785.
ICML-2019-XieKG #distributed #fault tolerance #named: Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance (CX, SK, IG), pp. 6893–6901.
ICML-2019-XuQLJY #convergence #optimisation: Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence (YX, QQ, QL, RJ, TY), pp. 6942–6951.
ICML-2019-YangZKBWS #precise: SWALP : Stochastic Weight Averaging in Low Precision Training (GY, TZ, PK, JB, AGW, CDS), pp. 7015–7024.
ICML-2019-YuJ #communication #complexity #on the #optimisation #parallel: On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization (HY, RJ), pp. 7174–7183.
ICML-2019-YurtseverSC #difference: Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator (AY, SS, VC), pp. 7282–7291.
ICML-2019-Zhou0Y #optimisation: Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization (BZ, FC0, YY), pp. 7563–7573.
ICML-2019-ZhuangCO #learning #online #optimisation: Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization (ZZ, AC, FO), pp. 7664–7672.
ICML-2019-ZhuWYWM #behaviour: The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects (ZZ, JW, BY, LW, JM), pp. 7654–7663.
ICML-2019-ZimmertLW: Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously (JZ, HL, CYW), pp. 7683–7692.
KDD-2019-GrislainPT #network #realtime: Recurrent Neural Networks for Stochastic Control in Real-Time Bidding (NG, NP0, AT), pp. 2801–2809.
KDD-2019-NosakhareP #behaviour #modelling: Probabilistic Latent Variable Modeling for Assessing Behavioral Influences on Well-Being (EN, RWP), pp. 2718–2726.
KDD-2019-SheetritNKS #predict: Temporal Probabilistic Profiles for Sepsis Prediction in the ICU (ES, NN, DK, YS), pp. 2961–2969.
KDD-2019-SuZNLSP #detection #multi #network #robust: Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network (YS, YZ, CN, RL, WS, DP), pp. 2828–2837.
KDD-2019-TariqLSLJCW #detection #multi #using: Detecting Anomalies in Space using Multivariate Convolutional LSTM with Mixtures of Probabilistic PCA (ST, SL, YS, MSL, OJ, DC, SSW), pp. 2123–2133.
Onward-2019-Tolpin #programming: Deployable probabilistic programming (DT), pp. 1–16.
OOPSLA-2019-Bastani0S #verification: Probabilistic verification of fairness properties via concentration (OB, XZ0, ASL), p. 27.
OOPSLA-2019-Huang0CG #composition #source code #termination #verification: Modular verification for almost-sure termination of probabilistic programs (MH, HF0, KC, AKG), p. 29.
PLDI-2019-Cusumano-Towner #named #programmable #programming: Gen: a general-purpose probabilistic programming system with programmable inference (MFCT, FAS, AKL, VKM), pp. 221–236.
PLDI-2019-SmolkaKKFHK0 #network #scalability #verification: Scalable verification of probabilistic networks (SS, PK0, DMK, NF, JH, DK, AS0), pp. 190–203.
PLDI-2019-Wang0GCQS #cost analysis #nondeterminism #source code: Cost analysis of nondeterministic probabilistic programs (PW, HF0, AKG, KC, XQ, WS), pp. 204–220.
PLDI-2019-ZhangX #incremental #source code: Incremental precision-preserving symbolic inference for probabilistic programs (JZ, JX), pp. 237–252.
POPL-2019-BatzKKMN #logic #pointer #reasoning #source code: Quantitative separation logic: a logic for reasoning about probabilistic pointer programs (KB, BLK, JPK, CM, TN0), p. 29.
POPL-2019-GorinovaGS #flexibility #performance #programming: Probabilistic programming with densities in SlicStan: efficient, flexible, and deterministic (MIG, ADG, CAS), p. 30.
POPL-2019-SaadCSRM #automation #modelling #source code #synthesis: Bayesian synthesis of probabilistic programs for automatic data modeling (FAS, MFCT, US, MCR, VKM), p. 32.
POPL-2019-SatoABGGH #approximate #convergence #higher-order #optimisation #reasoning #source code #verification: Formal verification of higher-order probabilistic programs: reasoning about approximation, convergence, Bayesian inference, and optimization (TS, AA0, GB, MG, DG0, JH), p. 30.
POPL-2019-SmithHA #abstraction: Trace abstraction modulo probability (CS, JH, AA), p. 31.
POPL-2019-VakarKS #programming #statistics: A domain theory for statistical probabilistic programming (MV, OK, SS), p. 29.
QAPL-2019-Kirkeby #analysis #reuse #source code: Probabilistic Output Analyses for Deterministic Programs - Reusing Existing Non-probabilistic Analyses (MHK), pp. 43–57.
ESEC-FSE-2019-DuttaZHM #debugging #named #programming #reduction #testing: Storm: program reduction for testing and debugging probabilistic programming systems (SD, WZ, ZH, SM), pp. 729–739.
ICSE-2019-MillerKSZZL: Probabilistic disassembly (KAM, YK, YS, ZZ0, XZ0, ZL), pp. 1187–1198.
ICSE-2019-WangWSTCS0WZL #algebra #optimisation #source code: Global optimization of numerical programs via prioritized stochastic algebraic transformations (XW, HW, ZS, ET, XC, WS, ZC0, LW, XZ, XL), pp. 1131–1141.
ASPLOS-2019-BanerjeeKI #algorithm #markov #modelling #monte carlo: AcMC 2 : Accelerating Markov Chain Monte Carlo Algorithms for Probabilistic Models (SSB, ZTK, RKI), pp. 515–528.
CASE-2019-MathesenYPF #adaptation #cyber-physical #nondeterminism #optimisation #quantifier #robust: Falsification of Cyber-Physical Systems with Robustness Uncertainty Quantification Through Stochastic optimization with Adaptive Restart (LM, SY, GP, GF), pp. 991–997.
ESOP-2019-CastellanP #programming #semantics: Probabilistic Programming Inference via Intensional Semantics (SC, HP), pp. 322–349.
CADE-2019-GieslGH #constant #source code: Computing Expected Runtimes for Constant Probability Programs (JG, PG, MH), pp. 269–286.
CAV-2019-AshokKW #game studies #markov #model checking #process #statistics: PAC Statistical Model Checking for Markov Decision Processes and Stochastic Games (PA, JK, MW), pp. 497–519.
CAV-2019-DrewsAD #constraints #performance #synthesis: Efficient Synthesis with Probabilistic Constraints (SD, AA, LD), pp. 278–296.
CAV-2019-HongLMR #bisimulation #protocol #verification: Probabilistic Bisimulation for Parameterized Systems - (with Applications to Verifying Anonymous Protocols) (CDH, AWL, RM, PR), pp. 455–474.
CAV-2019-NeupaneMM00 #analysis #approximate #infinity #model checking #named: STAMINA: STochastic Approximate Model-Checker for INfinite-State Analysis (TN, CJM, CM, HZ0, ZZ0), pp. 540–549.
VMCAI-2019-FoxSH #partial order #reachability: Syntactic Partial Order Compression for Probabilistic Reachability (GF, DS, HH), pp. 446–467.
VMCAI-2019-FuC #nondeterminism #source code #termination: Termination of Nondeterministic Probabilistic Programs (HF0, KC), pp. 468–490.
SANER-2018-SotoG #debugging #predict #using: Using a probabilistic model to predict bug fixes (MS, CLG), pp. 221–231.
CIAA-2018-CognettaH #online #pattern matching: Online Stochastic Pattern Matching (MC, YSH), pp. 121–132.
DLT-2018-CatalanoJ #matrix #set: The Synchronizing Probability Function for Primitive Sets of Matrices (CC, RMJ), pp. 194–205.
FSCD-2018-Vignudelli #equivalence #higher-order #proving: Proof Techniques for Program Equivalence in Probabilistic Higher-Order Languages (Invited Talk) (VV), p. 2.
IFM-2018-KangMH #constraints #using #verification: Probabilistic Verification of Timing Constraints in Automotive Systems Using UPPAAL-SMC (EYK0, DM, LH), pp. 236–254.
ICFP-2018-WandCGC #equivalence #random #recursion: Contextual equivalence for a probabilistic language with continuous random variables and recursion (MW, RC, TG, AC), p. 30.
CIKM-2018-AdigaCKMRRS #modelling #network #query #using: Inferring Probabilistic Contagion Models Over Networks Using Active Queries (AA, VCM, CJK, MVM, SSR, DJR, RES), pp. 377–386.
CIKM-2018-BonchiGMR #analysis #social: Probabilistic Causal Analysis of Social Influence (FB, FG, BM, DR), pp. 1003–1012.
CIKM-2018-Tang #network #social: Stochastic Coupon Probing in Social Networks (ST), pp. 1023–1031.
CIKM-2018-ZhangNCC #database #parallel #scalability #using: Scalable Entity Resolution Using Probabilistic Signatures on Parallel Databases (YZ, KSN, TC, PC), pp. 2213–2221.
ICML-2018-0001KS #named #optimisation: Shampoo: Preconditioned Stochastic Tensor Optimization (VG0, TK, YS), pp. 1837–1845.
ICML-2018-0004K #finite #infinity #lightweight #optimisation: Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data (SZ0, JTYK), pp. 5927–5935.
ICML-2018-Allen-Zhu #optimisation: Katyusha X: Practical Momentum Method for Stochastic Sum-of-Nonconvex Optimization (ZAZ), pp. 179–185.
ICML-2018-BallesH: Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients (LB, PH), pp. 413–422.
ICML-2018-ChatterjiFMBJ #formal method #monte carlo #on the #reduction: On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo (NSC, NF, YAM, PLB, MIJ), pp. 763–772.
ICML-2018-ChenHHK #online #optimisation: Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity (LC0, CH, HH, AK), pp. 813–822.
ICML-2018-ChenXCY #adaptation #named: SADAGRAD: Strongly Adaptive Stochastic Gradient Methods (ZC, YX, EC, TY), pp. 912–920.
ICML-2018-ChenZS #graph #network #reduction: Stochastic Training of Graph Convolutional Networks with Variance Reduction (JC, JZ0, LS), pp. 941–949.
ICML-2018-ClaiciCS: Stochastic Wasserstein Barycenters (SC, EC, JS), pp. 998–1007.
ICML-2018-DaneshmandKLH: Escaping Saddles with Stochastic Gradients (HD, JMK, AL, TH), pp. 1163–1172.
ICML-2018-DentonF #generative #video: Stochastic Video Generation with a Learned Prior (ED, RF), pp. 1182–1191.
ICML-2018-DoerrDSNSTT #modelling: Probabilistic Recurrent State-Space Models (AD, CD, MS, DNT, SS, MT, ST), pp. 1279–1288.
ICML-2018-DouikH #clustering #graph #matrix #optimisation #rank: Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering (AD, BH), pp. 1298–1307.
ICML-2018-GuHDH #algorithm #memory management #performance: Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines (BG, ZH, CD, HH), pp. 1807–1816.
ICML-2018-HaarnojaZAL #learning: Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor (TH, AZ, PA, SL), pp. 1856–1865.
ICML-2018-HoltzenBM #abstraction #composition #source code: Sound Abstraction and Decomposition of Probabilistic Programs (SH, GVdB, TDM), pp. 2004–2013.
ICML-2018-HuWL #analysis #reduction #source code #using: Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs (BH, SW, LL), pp. 2043–2052.
ICML-2018-KasaiSM #algorithm #analysis #convergence #recursion: Riemannian Stochastic Recursive Gradient Algorithm with Retraction and Vector Transport and Its Convergence Analysis (HK, HS, BM), pp. 2521–2529.
ICML-2018-KuzborskijL: Data-Dependent Stability of Stochastic Gradient Descent (IK, CHL), pp. 2820–2829.
ICML-2018-LianZZL #distributed #parallel: Asynchronous Decentralized Parallel Stochastic Gradient Descent (XL, WZ0, CZ, JL0), pp. 3049–3058.
ICML-2018-LinC #distributed #learning #multi: Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods (JL, VC), pp. 3098–3107.
ICML-2018-LiuH #performance #reduction: Fast Variance Reduction Method with Stochastic Batch Size (XL, CJH), pp. 3185–3194.
ICML-2018-LiuZCWY #performance: Fast Stochastic AUC Maximization with O(1/n)-Convergence Rate (ML, XZ, ZC, XW, TY), pp. 3195–3203.
ICML-2018-LorenziF #modelling: Constraining the Dynamics of Deep Probabilistic Models (ML, MF), pp. 3233–3242.
ICML-2018-MianjyA: Stochastic PCA with 𝓁2 and 𝓁1 Regularization (PM, RA), pp. 3528–3536.
ICML-2018-NatoleYL #algorithm: Stochastic Proximal Algorithms for AUC Maximization (MN, YY, SL), pp. 3707–3716.
ICML-2018-OkunoHS #framework #learning #multi #network: A probabilistic framework for multi-view feature learning with many-to-many associations via neural networks (AO, TH, HS), pp. 3885–3894.
ICML-2018-PapiniBCPR #policy: Stochastic Variance-Reduced Policy Gradient (MP, DB, GC, MP, MR), pp. 4023–4032.
ICML-2018-RuizTDB #category theory #scalability: Augment and Reduce: Stochastic Inference for Large Categorical Distributions (FJRR, MKT, ABD, DMB), pp. 4400–4409.
ICML-2018-RukatHY #composition: Probabilistic Boolean Tensor Decomposition (TR, CCH, CY), pp. 4410–4419.
ICML-2018-RyderGMP #black box #difference #equation: Black-Box Variational Inference for Stochastic Differential Equations (TR, AG, ASM, DP), pp. 4420–4429.
ICML-2018-ShenMZZQ #communication #convergence #distributed #learning #performance #towards: Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication (ZS, AM, TZ, PZ, HQ), pp. 4631–4640.
ICML-2018-SimsekliYNCR #optimisation: Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization (US, CY, THN, ATC, GR), pp. 4681–4690.
ICML-2018-VogelBC #learning #optimisation #similarity: A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization (RV, AB, SC), pp. 5062–5071.
ICML-2018-WuSHDR #algorithm #programming #semantics: Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms (YW, SS, NH, SD, SJR), pp. 5339–5348.
ICML-2018-XuWG: Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions (PX0, TW0, QG), pp. 5488–5497.
ICML-2018-ZhouSC #algorithm #convergence #performance: A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates (KZ, FS, JC), pp. 5975–5984.
ICML-2018-ZhouXG #polynomial: Stochastic Variance-Reduced Cubic Regularized Newton Method (DZ, PX0, QG), pp. 5985–5994.
ICML-2018-ZouXG #monte carlo: Stochastic Variance-Reduced Hamilton Monte Carlo Methods (DZ, PX0, QG), pp. 6023–6032.
ICPR-2018-ChoiCT #authentication #mobile #network #random: One-class Random Maxout Probabilistic Network for Mobile Touchstroke Authentication (SC, IC, ABJT), pp. 3359–3364.
ICPR-2018-GaoCMXL #visual notation: Deep Pixel Probabilistic Model for Super Resolution Based on Human Visual Saliency Mechanism (HG, ZC, GM, WX, ZL), pp. 2747–2752.
ICPR-2018-JaberiPF #clustering #using: Probabilistic Sparse Subspace Clustering Using Delayed Association (MJ, MP, HF), pp. 2087–2092.
ICPR-2018-XiaoDYLZW #adaptation #graph: Probabilistic Graph Embedding for Unsupervised Domain Adaptation (PX, BD, SY, XL, YZ, JW0), pp. 1283–1288.
ICPR-2018-XinCZYW #recognition #sequence #visual notation: Probabilistic Voting for Sequence Based Visual Place Recognition (ZX, YC, JZ0, YY, YW), pp. 1791–1796.
KDD-2018-0001C #performance #recommendation: Efficient Attribute Recommendation with Probabilistic Guarantee (CW0, KC), pp. 2387–2396.
KDD-2018-HuaiMLSSZ #learning #metric: Metric Learning from Probabilistic Labels (MH, CM, YL, QS, LS, AZ), pp. 1541–1550.
OOPSLA-2018-OzkanMNBW #distributed #random #testing: Randomized testing of distributed systems with probabilistic guarantees (BKO, RM, FN, MTB, GW), p. 28.
PADL-2018-DylusCT #functional #logic programming: Probabilistic Functional Logic Programming (SD, JC, FT), pp. 3–19.
PLDI-2018-Cusumano-Towner18a #incremental #source code: Incremental inference for probabilistic programs (MCT, BB, TG, MTV, VKM), pp. 571–585.
PLDI-2018-GehrMTVWV #named #network: Bayonet: probabilistic inference for networks (TG, SM, PT, LV, PW, MTV), pp. 586–602.
PLDI-2018-LeeHAN #modelling #search-based #synthesis #using: Accelerating search-based program synthesis using learned probabilistic models (WL, KH, RA, MN), pp. 436–449.
PLDI-2018-MansinghkaSHRCR #programmable #programming: Probabilistic programming with programmable inference (VKM, US, SH, AR, YC, MR), pp. 603–616.
PLDI-2018-NgoC0 #analysis #bound #source code: Bounded expectations: resource analysis for probabilistic programs (VCN, QC, JH0), pp. 496–512.
PLDI-2018-WangHR #algebra #framework #named #source code #static analysis: PMAF: an algebraic framework for static analysis of probabilistic programs (DW, JH0, TWR), pp. 513–528.
POPL-2018-AgrawalC0 #approach #performance #ranking #source code #termination: Lexicographic ranking supermartingales: an efficient approach to termination of probabilistic programs (SA, KC, PN0), p. 32.
POPL-2018-BartheEGHS #proving #source code: Proving expected sensitivity of probabilistic programs (GB, TE, BG, JH, PYS), p. 29.
POPL-2018-EhrhardPT #higher-order #programming: Measurable cones and stable, measurable functions: a model for probabilistic higher-order programming (TE, MP, CT), p. 28.
PPDP-2018-BreuvartL #on the #λ-calculus: On Intersection Types and Probabilistic Lambda Calculi (FB, UDL), p. 13.
ESEC-FSE-2018-CaninoLM #energy #mobile #optimisation: Stochastic energy optimization for mobile GPS applications (AC, YDL, HM), pp. 703–713.
ESEC-FSE-2018-DuttaLHM #programming #testing: Testing probabilistic programming systems (SD0, OL, ZH, SM), pp. 574–586.
ESEC-FSE-2018-KateOZEX #consistency #detection #named #nondeterminism #physics: Phys: probabilistic physical unit assignment and inconsistency detection (SK, JPO, XZ, SGE, ZX), pp. 563–573.
ESEC-FSE-2018-LlerenaBBSR #behaviour #modelling #nondeterminism #verification: Verifying the long-run behavior of probabilistic system models in the presence of uncertainty (YRSL, MB, MB, GS, DSR), pp. 587–597.
ICSE-2018-XuMZZX #debugging: Debugging with intelligence via probabilistic inference (ZX, SM, XZ0, SZ, BX), pp. 1171–1181.
CASE-2018-FrancoAGABB #approach #deployment #optimisation #using: Strategic territorial deployment of hospital pharmacy robots using a stochastic p-robust optimization approach (CF, VA, TG, EAL, MB, HB), pp. 390–395.
CASE-2018-LaiPPHM #estimation #linear: Probabilistic Pose Estimation of Deformable Linear Objects (YL, JP, GP, HH, TM), pp. 471–476.
CASE-2018-LiXPC #markov #performance: Efficient Sampling Procedure for Selecting the Largest Stationary Probability of a Markov Chain (HL, XX, YP, CHC), pp. 899–905.
CASE-2018-SundstromWL #energy #performance #robust: Robust and Energy Efficient Trajectories in a Stochastic Common Workspace Setting (NS, OW, BL), pp. 77–83.
ESOP-2018-0001BBBG0 #markov #reasoning #relational #λ-calculus: Relational Reasoning for Markov Chains in a Probabilistic Guarded Lambda Calculus (AA0, GB, LB, AB, MG, DG0), pp. 214–241.
ESOP-2018-BartheEGGHS #logic #source code: An Assertion-Based Program Logic for Probabilistic Programs (GB, TE, MG, BG, JH, PYS), pp. 117–144.
ESOP-2018-BichselGV #fine-grained #semantics #source code: Fine-Grained Semantics for Probabilistic Programs (BB, TG, MTV), pp. 145–185.
CAV-2018-KelmendiKKW #algorithm #game studies #learning: Value Iteration for Simple Stochastic Games: Stopping Criterion and Learning Algorithm (EK, JK, JK, MW), pp. 623–642.
CAV-2018-TangB #distance #markov #similarity: Deciding Probabilistic Bisimilarity Distance One for Labelled Markov Chains (QT0, FvB), pp. 681–699.
CSL-2018-ChadhaS0 #approximate #automaton #regular expression: Approximating Probabilistic Automata by Regular Languages (RC, APS, MV0), p. 23.
CSL-2018-ClairambaultP #modelling #λ-calculus: Fully Abstract Models of the Probabilistic lambda-calculus (PC, HP), p. 17.
CSL-2018-LopezS #algebra #nondeterminism: Basic Operational Preorders for Algebraic Effects in General, and for Combined Probability and Nondeterminism in Particular (AL, AS), p. 17.
IJCAR-2018-FingerP #logic #satisfiability: Probably Half True: Probabilistic Satisfiability over Łukasiewicz Infinitely-Valued Logic (MF, SP), pp. 194–210.
IJCAR-2018-GeMLZM #algorithm #approximate: A New Probabilistic Algorithm for Approximate Model Counting (CG, FM, TL, JZ0, XM), pp. 312–328.
VMCAI-2018-ZuckMT #protocol #proving: P^5 : Planner-less Proofs of Probabilistic Parameterized Protocols (LDZ, KLM, JT), pp. 336–357.
SANER-2017-TangL #approach #mining #named #novel #using: StiCProb: A novel feature mining approach using conditional probability (YT, HL), pp. 45–55.
CIAA-2017-CauliP #calculus #equivalence #μ-calculus: Equivalence of Probabilistic μ-Calculus and p-Automata (CC, NP), pp. 64–75.
DLT-2017-Yamakami #automaton #bound #complexity: One-Way Bounded-Error Probabilistic Pushdown Automata and Kolmogorov Complexity - (Preliminary Report) (TY), pp. 353–364.
FSCD-2017-Tasson #programming #semantics: Quantitative Semantics for Probabilistic Programming (Invited Talk) (CT), p. 1.
ICFP-2017-NarayananS #array #source code: Symbolic conditioning of arrays in probabilistic programs (PN, CcS), p. 25.
CIKM-2017-Chekol #evaluation #query #scalability: Scaling Probabilistic Temporal Query Evaluation (MWC), pp. 697–706.
CIKM-2017-HuLSLL0Z #approach #information management #named #segmentation: CNN-IETS: A CNN-based Probabilistic Approach for Information Extraction by Text Segmentation (MH, ZL, YS, AL0, GL0, KZ0, LZ0), pp. 1159–1168.
CIKM-2017-ZhangGHCL #semistructured data: Probabilistic Skyline on Incomplete Data (KZ, HG, XH, ZC, JL), pp. 427–436.
CIKM-2017-ZhongLCWWAF #knowledge base #named #online: POOLSIDE: An Online Probabilistic Knowledge Base for Shopping Decision Support (PZ, ZL, QC, YW, LW, MHMA, FF), pp. 2559–2562.
ICML-2017-Allen-Zhu #named #optimisation #parametricity #performance: Natasha: Faster Non-Convex Stochastic Optimization via Strongly Non-Convex Parameter (ZAZ), pp. 89–97.
ICML-2017-BeckhamP #classification: Unimodal Probability Distributions for Deep Ordinal Classification (CB, CJP), pp. 411–419.
ICML-2017-ChouMS #learning #policy #using: Improving Stochastic Policy Gradients in Continuous Control with Deep Reinforcement Learning using the Beta Distribution (PWC, DM, SAS), pp. 834–843.
ICML-2017-CongCLZ #adaptation #topic: Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC (YC, BC0, HL, MZ), pp. 864–873.
ICML-2017-DaiGKHS #generative: Stochastic Generative Hashing (BD, RG, SK, NH, LS), pp. 913–922.
ICML-2017-DinhBZM #monte carlo: Probabilistic Path Hamiltonian Monte Carlo (VD, AB, CZ, FAMI), pp. 1009–1018.
ICML-2017-DuCLXZ #evaluation #policy #reduction: Stochastic Variance Reduction Methods for Policy Evaluation (SSD, JC, LL0, LX, DZ), pp. 1049–1058.
ICML-2017-GarberSS #algorithm #analysis #component #distributed: Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis (DG, OS, NS), pp. 1203–1212.
ICML-2017-HassidimS #algorithm #robust: Robust Guarantees of Stochastic Greedy Algorithms (AH, YS), pp. 1424–1432.
ICML-2017-LanPZZ #lazy evaluation: Conditional Accelerated Lazy Stochastic Gradient Descent (GL, SP, YZ, DZ), pp. 1965–1974.
ICML-2017-LiTE #adaptation #algorithm #equation: Stochastic Modified Equations and Adaptive Stochastic Gradient Algorithms (QL, CT, WE), pp. 2101–2110.
ICML-2017-MaFF #markov #modelling: Stochastic Gradient MCMC Methods for Hidden Markov Models (YAM, NJF, EBF), pp. 2265–2274.
ICML-2017-NguyenLST #machine learning #named #novel #problem #recursion #using: SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient (LMN, JL, KS, MT), pp. 2613–2621.
ICML-2017-PakmanGCP: Stochastic Bouncy Particle Sampler (AP, DG, DEC, LP), pp. 2741–2750.
ICML-2017-PanahiDJB #algorithm #clustering #convergence #incremental: Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery (AP, DPD, FDJ, CB), pp. 2769–2777.
ICML-2017-Simsekli #difference #equation #markov #monte carlo: Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for Markov Chain Monte Carlo (US), pp. 3200–3209.
ICML-2017-StanZ0K: Probabilistic Submodular Maximization in Sub-Linear Time (SS, MZ, AK0, AK), pp. 3241–3250.
ICML-2017-TaiebTH: Coherent Probabilistic Forecasts for Hierarchical Time Series (SBT, JWT, RJH), pp. 3348–3357.
ICML-2017-ThiLNT #classification #problem: Stochastic DCA for the Large-sum of Non-convex Functions Problem and its Application to Group Variable Selection in Classification (HALT, HML, PDN, BT), pp. 3394–3403.
ICML-2017-UmlauftH #learning: Learning Stable Stochastic Nonlinear Dynamical Systems (JU, SH), pp. 3502–3510.
ICML-2017-WangKB #modelling #robust: Robust Probabilistic Modeling with Bayesian Data Reweighting (YW, AK, DMB), pp. 3646–3655.
ICML-2017-XuLY #convergence #optimisation #performance: Stochastic Convex Optimization: Faster Local Growth Implies Faster Global Convergence (YX, QL, TY), pp. 3821–3830.
ICML-2017-ZhangCGHC: Stochastic Gradient Monomial Gamma Sampler (YZ, CC, ZG, RH, LC), pp. 3996–4005.
ICML-2017-ZhengMWCYML: Asynchronous Stochastic Gradient Descent with Delay Compensation (SZ, QM, TW, WC0, NY, ZM, TYL), pp. 4120–4129.
ICML-2017-ZhouGG #adaptation: Stochastic Adaptive Quasi-Newton Methods for Minimizing Expected Values (CZ, WG, DG), pp. 4150–4159.
ICML-2017-ZhuWZG #algorithm: High-Dimensional Variance-Reduced Stochastic Gradient Expectation-Maximization Algorithm (RZ, LW, CZ, QG), pp. 4180–4188.
ICML-2017-ZoghiTGKSW #learning #modelling #online #rank: Online Learning to Rank in Stochastic Click Models (MZ, TT, MG, BK, CS, ZW), pp. 4199–4208.
KDD-2017-ShiCZG0 #named #network: PReP: Path-Based Relevance from a Probabilistic Perspective in Heterogeneous Information Networks (YS, PWC, HZ, HG, JH0), pp. 425–434.
ECMFA-2017-Debbi #analysis #formal method #modelling: Modeling and Formal Analysis of Probabilistic Complex Event Processing (CEP) Applications (HD), pp. 248–263.
OOPSLA-2017-AlbarghouthiDDN #named #verification: FairSquare: probabilistic verification of program fairness (AA, LD, SD, AVN), p. 30.
AdaEurope-2017-DiazFKMHAC #analysis #bound #manycore #named: MC2: Multicore and Cache Analysis via Deterministic and Probabilistic Jitter Bounding (ED, MF, LK, EM, CH, JA, FJC), pp. 102–118.
PADL-2017-MantadelisR #logic #using: Using Iterative Deepening for Probabilistic Logic Inference (TM, RR0), pp. 198–213.
PLDI-2017-HuangTM #algorithm #compilation #markov #modelling #monte carlo: Compiling Markov chain Monte Carlo algorithms for probabilistic modeling (DH0, JBT, GM), pp. 111–125.
POPL-2017-BartheGHS #proving #source code: Coupling proofs are probabilistic product programs (GB, BG, JH, PYS), pp. 161–174.
POPL-2017-ChatterjeeNZ #invariant #termination: Stochastic invariants for probabilistic termination (KC, PN0, DZ), pp. 145–160.
POPL-2017-LagoFVY #geometry #parallel #quantum: The geometry of parallelism: classical, probabilistic, and quantum effects (UDL, CF, BV, AY), pp. 833–845.
POPL-2017-SmolkaKFK0 #network #semantics: Cantor meets scott: semantic foundations for probabilistic networks (SS, PK0, NF, DK, AS0), pp. 557–571.
SAS-2017-Albarghouthi #horn clause #verification: Probabilistic Horn Clause Verification (AA), pp. 1–22.
SAS-2017-ZhangSX #analysis #incremental #source code: Incremental Analysis for Probabilistic Programs (JZ, YS, JX), pp. 450–472.
ESEC-FSE-2017-LlerenaSR #in the cloud #model checking: Probabilistic model checking of perturbed MDPs with applications to cloud computing (YRSL, GS, DSR), pp. 454–464.
ESEC-FSE-2017-SuMCWYYPLS #android #modelling #testing #user interface: Guided, stochastic model-based GUI testing of Android apps (TS, GM, YC, KW, WY, YY, GP, YL0, ZS), pp. 245–256.
ICSE-2017-LiuSSJGS #obfuscation #optimisation: Stochastic optimization of program obfuscation (HL0, CS, ZS, YJ0, MG0, JS), pp. 221–231.
ASPLOS-2017-RenLDQWLQY #named #network #using: SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing (AR, ZL0, CD, QQ, YW, JL0, XQ, BY0), pp. 405–418.
CASE-2017-ChenWC #multi #policy: Steady state probability distribution of a two-product-type and multi-parallel-machine system under prioritized hedging point control policy (WC, ZW, FTSC), pp. 224–230.
CASE-2017-LiuJXX #higher-order #performance: Fast terminal sliding mode control of high-order stochastic systems (XL, XJ, LX, HX), pp. 1592–1597.
CASE-2017-ProdelAXJL #database #health #simulation: Stochastic simulation of clinical pathways from raw health databases (MP, VA, XX, BJ, LL), pp. 580–585.
CASE-2017-WangFFLC #energy #markov: Markov chain based idle status control of stochastic machines for energy saving operation (JW, YF, ZF, SL, QC), pp. 1019–1023.
CASE-2017-ZhaoZS: Probabilistic abnormal glycemic event alert for T1DM patients (HZ, CZ, YS), pp. 795–800.
ESOP-2017-CulpepperC #equivalence #random #source code: Contextual Equivalence for Probabilistic Programs with Continuous Random Variables and Scoring (RC, AC), pp. 368–392.
ESOP-2017-LagoG #monad #termination #type system: Probabilistic Termination by Monadic Affine Sized Typing (UDL, CG), pp. 393–419.
ESOP-2017-Staton #commutative #programming #semantics: Commutative Semantics for Probabilistic Programming (SS), pp. 855–879.
FASE-2017-Wang0YP #approach #empirical #model checking #modelling: Should We Learn Probabilistic Models for Model Checking? A New Approach and An Empirical Study (JW, JS0, QY, JP0), pp. 3–21.
CAV-2017-ChasinsP #data-driven #source code #synthesis: Data-Driven Synthesis of Full Probabilistic Programs (SC, PMP), pp. 279–304.
CAV-2017-DehnertJK0 #model checking: A Storm is Coming: A Modern Probabilistic Model Checker (CD, SJ, JPK, MV0), pp. 592–600.
ICST-2017-PatrickDG #simulation #statistics #testing #tool support: A Toolkit for Testing Stochastic Simulations against Statistical Oracles (MP, RD, CAG), pp. 448–453.
ICTSS-2017-SchumiLAKS: Checking Response-Time Properties of Web-Service Applications Under Stochastic User Profiles (RS, PL, BKA, WK, RS), pp. 293–310.
TAP-2017-GerholdS #modelling #testing: Model-Based Testing of Probabilistic Systems with Stochastic Time (MG, MS), pp. 77–97.
IFM-2016-AndreiCCMR #analysis #formal method: Probabilistic Formal Analysis of App Usage to Inform Redesign (OA, MC, MC, AM, MR), pp. 115–129.
IFM-2016-DArgenioHLS #approximate #automaton #statistics: Statistical Approximation of Optimal Schedulers for Probabilistic Timed Automata (PRD, AH, AL, SS), pp. 99–114.
ICFP-2016-BorgstromLGS #programming #λ-calculus: A lambda-calculus foundation for universal probabilistic programming (JB, UDL, ADG, MS), pp. 33–46.
ICFP-2016-IsmailS #functional: Deriving a probability density calculator (functional pearl) (WMI, CcS), pp. 47–59.
AIIDE-2016-UriarteO #modelling #monte carlo #policy: Improving Monte Carlo Tree Search Policies in StarCraft via Probabilistic Models Learned from Replay Data (AU, SO), pp. 100–106.
CIKM-2016-AnavaSKR #framework: A Probabilistic Fusion Framework (YA, AS, OK, ER), pp. 1463–1472.
CIKM-2016-JangFDA #detection: Probabilistic Approaches to Controversy Detection (MJ, JF, SDH, JA), pp. 2069–2072.
CIKM-2016-JiWZ #multi #online: A Probabilistic Multi-Touch Attribution Model for Online Advertising (WJ, XW, DZ), pp. 1373–1382.
CIKM-2016-KimXO #composition #graph #incremental: Probabilistic Knowledge Graph Construction: Compositional and Incremental Approaches (DK0, LX, CSO), pp. 2257–2262.
CIKM-2016-LinZC #comprehension #topic: Understanding Sparse Topical Structure of Short Text via Stochastic Variational-Gibbs Inference (TL, SZ, HC), pp. 407–416.
CIKM-2016-RekabsazLHZ #framework #modelling: Generalizing Translation Models in the Probabilistic Relevance Framework (NR, ML, AH, GZ), pp. 711–720.
CIKM-2016-ZhengC #classification #constraints #learning: Regularizing Structured Classifier with Conditional Probabilistic Constraints for Semi-supervised Learning (VWZ, KCCC), pp. 1029–1038.
ECIR-2016-ChenJYYZ #graph #modelling #semantics #topic: Probabilistic Topic Modelling with Semantic Graph (LC0, JMJ, HY, FY, HZ), pp. 240–251.
ECIR-2016-HeHSH: Estimating Probability Density of Content Types for Promoting Medical Records Search (YH, QH, YS, LH0), pp. 252–263.
ECIR-2016-LiEV #retrieval: Probabilistic Local Expert Retrieval (WL, CE, APdV), pp. 227–239.
ECIR-2016-OosterhuisSR #multi: Probabilistic Multileave Gradient Descent (HO, AS, MdR), pp. 661–668.
ICML-2016-AroraMM #learning #multi #optimisation #representation #using: Stochastic Optimization for Multiview Representation Learning using Partial Least Squares (RA, PM, TVM), pp. 1786–1794.
ICML-2016-BielikRV #named: PHOG: Probabilistic Model for Code (PB, VR, MTV), pp. 2933–2942.
ICML-2016-Curtis #algorithm #optimisation #self: A Self-Correcting Variable-Metric Algorithm for Stochastic Optimization (FC), pp. 632–641.
ICML-2016-DegenneP #algorithm #multi: Anytime optimal algorithms in stochastic multi-armed bandits (RD, VP), pp. 1587–1595.
ICML-2016-GlaudeP #automaton #learning: PAC learning of Probabilistic Automaton based on the Method of Moments (HG, OP), pp. 820–829.
ICML-2016-GowerGR: Stochastic Block BFGS: Squeezing More Curvature out of Data (RMG, DG, PR), pp. 1869–1878.
ICML-2016-HardtRS #performance: Train faster, generalize better: Stability of stochastic gradient descent (MH, BR, YS), pp. 1225–1234.
ICML-2016-HazanL #optimisation: Variance-Reduced and Projection-Free Stochastic Optimization (EH, HL), pp. 1263–1271.
ICML-2016-HazanLS #on the #optimisation #problem: On Graduated Optimization for Stochastic Non-Convex Problems (EH, KYL, SSS), pp. 1833–1841.
ICML-2016-JasinskaDBPKH #using: Extreme F-measure Maximization using Sparse Probability Estimates (KJ, KD, RBF, KP, TK, EH), pp. 1435–1444.
ICML-2016-LeeLO #process: Hawkes Processes with Stochastic Excitations (YL, KWL, CSO), pp. 79–88.
ICML-2016-LiZALH #learning #optimisation: Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning (XL, TZ, RA, HL0, JDH), pp. 917–925.
ICML-2016-MandtHB #algorithm #analysis: A Variational Analysis of Stochastic Gradient Algorithms (SM, MDH, DMB), pp. 354–363.
ICML-2016-PiatkowskiM: Stochastic Discrete Clenshaw-Curtis Quadrature (NP, KM), pp. 3000–3009.
ICML-2016-QuRTF #empirical #named: SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization (ZQ, PR, MT, OF), pp. 1823–1832.
ICML-2016-QuXO #algorithm #analysis #optimisation #performance: Fast Rate Analysis of Some Stochastic Optimization Algorithms (CQ, HX, CJO), pp. 662–670.
ICML-2016-ReddiHSPS #optimisation #reduction: Stochastic Variance Reduction for Nonconvex Optimization (SJR, AH, SS, BP, AJS), pp. 314–323.
ICML-2016-Shamir #algorithm #convergence #performance: Fast Stochastic Algorithms for SVD and PCA: Convergence Properties and Convexity (OS), pp. 248–256.
ICML-2016-Shamir16a #convergence: Convergence of Stochastic Gradient Descent for PCA (OS), pp. 257–265.
ICML-2016-SimsekliBCR #monte carlo: Stochastic Quasi-Newton Langevin Monte Carlo (US, RB, ATC, GR), pp. 642–651.
ICML-2016-WangWP: The Knowledge Gradient for Sequential Decision Making with Stochastic Binary Feedbacks (YW, CW, WBP), pp. 1138–1147.
ICML-2016-XuZCL #matrix #optimisation: Matrix Eigen-decomposition via Doubly Stochastic Riemannian Optimization (ZX, PZ, JC, XL0), pp. 1660–1669.
ICML-2016-ZhangYJXZ #feedback #linear #online #optimisation: Online Stochastic Linear Optimization under One-bit Feedback (LZ0, TY, RJ, YX, ZHZ), pp. 392–401.
ICPR-2016-BachaAB #recognition #using #visual notation: Event recognition in photo albums using probabilistic graphical model and feature relevance (SB, MSA, NB), pp. 2819–2823.
ICPR-2016-DanelljanMKF #set: Aligning the dissimilar: A probabilistic method for feature-based point set registration (MD, GM, FSK, MF), pp. 247–252.
ICPR-2016-HajduTKH #approach #constraints #execution: Composing ensembles by a stochastic approach under execution time constraint (AH, HT, LK, LH), pp. 222–227.
ICPR-2016-LuoLQ #analysis #bound #optimisation: Bound analysis of natural gradient descent in stochastic optimization setting (ZL, DL, YQ), pp. 4166–4171.
KDD-2016-WangNH #clustering #graph #matrix: Structured Doubly Stochastic Matrix for Graph Based Clustering: Structured Doubly Stochastic Matrix (XW, FN, HH), pp. 1245–1254.
KDD-2016-WuMSZZCW #robust: Probabilistic Robust Route Recovery with Spatio-Temporal Dynamics (HW0, JM, WS, BZ, HZ, ZC, WW0), pp. 1915–1924.
KDD-2016-Yang0Z #scalability: Distributing the Stochastic Gradient Sampler for Large-Scale LDA (YY, JC0, JZ0), pp. 1975–1984.
KDD-2016-ZhangG #coordination: Accelerated Stochastic Block Coordinate Descent with Optimal Sampling (AZ, QG), pp. 2035–2044.
OOPSLA-2016-RaychevBV: Probabilistic model for code with decision trees (VR, PB, MTV), pp. 731–747.
PADL-2016-CaretteS #algebra #source code #using: Simplifying Probabilistic Programs Using Computer Algebra (JC, CcS), pp. 135–152.
POPL-2016-BorgstromGORSS #named #programming: Fabular: regression formulas as probabilistic programming (JB, ADG, LO, CVR, AS, MS), pp. 271–283.
POPL-2016-ChatterjeeFNH #algorithm #analysis #problem #source code #termination: Algorithmic analysis of qualitative and quantitative termination problems for affine probabilistic programs (KC, HF0, PN0, RH), pp. 327–342.
POPL-2016-GrigoreY #abstraction #refinement: Abstraction refinement guided by a learnt probabilistic model (RG, HY), pp. 485–498.
POPL-2016-OcteauJDMB0KT #android #component #modelling #static analysis: Combining static analysis with probabilistic models to enable market-scale Android inter-component analysis (DO, SJ, MD, PDM, AB, LL0, JK, YLT), pp. 469–484.
POPL-2016-SangiorgiV #bisimulation #higher-order: Environmental bisimulations for probabilistic higher-order languages (DS, VV), pp. 595–607.
QAPL-2016-KlebanovWW #satisfiability: Sound Probabilistic #SAT with Projection (VK, AW, JW), pp. 15–29.
ASE-2016-CaiY #testing: Radius aware probabilistic testing of deadlocks with guarantees (YC, ZY), pp. 356–367.
ASE-2016-Rosenblum #power of: The power of probabilistic thinking (DSR), p. 3.
FSE-2016-FowkesS #api #git #mining: Parameter-free probabilistic API mining across GitHub (JMF, CAS), pp. 254–265.
FSE-2016-XuZCPX #natural language #python #type inference: Python probabilistic type inference with natural language support (ZX, XZ0, LC0, KP, BX), pp. 607–618.
ICSE-2016-ChenLL #execution #generative #performance #symbolic computation: Generating performance distributions via probabilistic symbolic execution (BC0, YL0, WL), pp. 49–60.
ICSE-2016-TanCSLAXD #optimisation #refinement: Optimizing selection of competing services with probabilistic hierarchical refinement (THT, MC, JS0, YL0, ÉA, YX, JSD), pp. 85–95.
CASE-2016-AntunesCB #analysis #performance #petri net: A stochastic Petri net model for simulation-based performance analysis of public bicycle sharing systems (IA, LKC, JCB), pp. 433–439.
CASE-2016-ChuSS #modelling #predict #realtime: Stochastic Lagrangian Traffic flow modeling and real-time traffic prediction (KCC, RS, KS), pp. 213–218.
CASE-2016-RonB #identification #industrial #modelling: Stochastic modelling and identification of industrial robots (MR, PB), pp. 342–347.
CASE-2016-ZhaoXL #constraints #effectiveness #order #throughput: Effective throughput maximization of stochastic customer orders with inventory constraints (YZ, XX, HL), pp. 1387–1393.
ESOP-2016-FosterKMR0: Probabilistic NetKAT (NF, DK, KM, MR, AS0), pp. 282–309.
ESOP-2016-HuangM #programming language #semantics: An Application of Computable Distributions to the Semantics of Probabilistic Programming Languages (DH0, GM), pp. 337–363.
ESOP-2016-KaminskiKMO #reasoning #source code: Weakest Precondition Reasoning for Expected Run-Times of Probabilistic Programs (BLK, JPK, CM, FO), pp. 364–389.
ESOP-2016-Lochbihler #encryption #higher-order #logic: Probabilistic Functions and Cryptographic Oracles in Higher Order Logic (AL), pp. 503–531.
FASE-2016-ChrszonDKB #analysis #modelling: Family-Based Modeling and Analysis for Probabilistic Systems - Featuring ProFeat (PC, CD, SK, CB), pp. 287–304.
FASE-2016-GerholdS #modelling #testing: Model-Based Testing of Probabilistic Systems (MG, MS), pp. 251–268.
CAV-2016-BartheEFH #composition #invariant: Synthesizing Probabilistic Invariants via Doob's Decomposition (GB, TE, LMFF, JH), pp. 43–61.
CAV-2016-ChatterjeeFG #analysis #source code #termination: Termination Analysis of Probabilistic Programs Through Positivstellensatz's (KC, HF0, AKG), pp. 3–22.
CAV-2016-GehrMV #named #source code: PSI: Exact Symbolic Inference for Probabilistic Programs (TG, SM, MTV), pp. 62–83.
CAV-2016-NgoLJ #modelling #named #runtime #verification: PSCV: A Runtime Verification Tool for Probabilistic SystemC Models (VCN, AL, VJ), pp. 84–91.
CAV-2016-HahnSTZ #algorithm #game studies: A Simple Algorithm for Solving Qualitative Probabilistic Parity Games (EMH, SS, AT, LZ0), pp. 291–311.
CAV-2016-SantolucitoZP #automation #learning: Probabilistic Automated Language Learning for Configuration Files (MS, EZ, RP), pp. 80–87.
CSL-2016-AlmagorK #synthesis: High-Quality Synthesis Against Stochastic Environments (SA, OK), p. 17.
VMCAI-2016-HashemiH0 #bound #nondeterminism #reachability: Reward-Bounded Reachability Probability for Uncertain Weighted MDPs (VH, HH, LS0), pp. 351–371.
CBSE-2015-KimBNMLSLP #analysis #scheduling: Quantitative Schedulability Analysis of Continuous Probability Tasks in a Hierarchical Context (JHK, AB, UN, MM, KGL, AS, IL, LTXP), pp. 91–100.
CBSE-2015-NandiMO #component #contract #realtime #runtime: Stochastic Contracts for Runtime Checking of Component-based Real-time Systems (CN, AM, MO), pp. 111–116.
JCDL-2015-PintoB #approach #semantics: Demystifying the Semantics of Relevant Objects in Scholarly Collections: A Probabilistic Approach (JMGP, WTB), pp. 157–164.
SIGMOD-2015-PengW #query: k-Hit Query: Top-k Query with Probabilistic Utility Function (PP, RCWW), pp. 577–592.
VLDB-2015-GatterbauerS #approximate #database: Approximate Lifted Inference with Probabilistic Databases (WG, DS), pp. 629–640.
VLDB-2015-ParkMS #pipes and filters #query #using: Processing of Probabilistic Skyline Queries Using MapReduce (YP, JKM, KS), pp. 1406–1417.
VLDB-2015-VattaniCL: Optimal Probabilistic Cache Stampede Prevention (AV, FC, KL), pp. 886–897.
EDM-2015-ChenWL #mining: Discovering Prerequisite Structure of Skills through Probabilistic Association Rules Mining (YC0, PHW, JML), pp. 117–124.
EDM-2015-GoutteLD #component: A Probabilistic Model for Knowledge Component Naming (CG, SL, GD), pp. 608–609.
EDM-2015-PriceLBC #algorithm #data-driven: An Improved Data-Driven Hint Selection Algorithm for Probability Tutors (TWP, CL, TB, MC), pp. 610–611.
DLT-2015-GainutdinovaY #automaton #problem #quantum: Unary Probabilistic and Quantum Automata on Promise Problems (AG, AY), pp. 252–263.
ICALP-v1-2015-DoronT #approximate #graph #on the #problem: On the Problem of Approximating the Eigenvalues of Undirected Graphs in Probabilistic Logspace (DD, ATS), pp. 419–431.
ICALP-v1-2015-HuangL #approximate #combinator #optimisation #problem: Approximating the Expected Values for Combinatorial Optimization Problems over Stochastic Points (LH, JL), pp. 910–921.
ICALP-v2-2015-Boreale #analysis #approximate #generative: Analysis of Probabilistic Systems via Generating Functions and Padé Approximation (MB), pp. 82–94.
ICALP-v2-2015-Chatterjee0V #complexity #component #synthesis: The Complexity of Synthesis from Probabilistic Components (KC, LD, MYV), pp. 108–120.
ICALP-v2-2015-EtessamiSY #branch #equation #fixpoint #markov #polynomial #process #reachability: Greatest Fixed Points of Probabilistic Min/Max Polynomial Equations, and Reachability for Branching Markov Decision Processes (KE, AS, MY), pp. 184–196.
LATA-2015-GonzeJ #on the: On the Synchronizing Probability Function and the Triple Rendezvous Time — New Approaches to Černý’s Conjecture (FG, RMJ), pp. 212–223.
FM-2015-EisentrautGHS0 #bisimulation: Probabilistic Bisimulation for Realistic Schedulers (CE, JCG, HH, LS, LZ), pp. 248–264.
Haskell-2015-ScibiorGG #monad #programming: Practical probabilistic programming with monads (AS, ZG, ADG), pp. 165–176.
CHI-2015-SchwarzMH #architecture #feedback #generative #interactive #user interface: An Architecture for Generating Interactive Feedback in Probabilistic User Interfaces (JS, JM, SEH), pp. 2545–2554.
HCI-UC-2015-FrauCT #mobile #predict #prototype #visualisation: Graphic Visualization of Probabilistic Traffic/Trajectory Predictions in Mobile Applications. A First Prototype and Evaluations for General Aviation Purposes (GF, FDC, DT), pp. 154–164.
CAiSE-2015-BrownL #quality: Probabilistic Keys for Data Quality Management (PB, SL), pp. 118–132.
CIKM-2015-GastMRT: Probabilistic Forecasts of Bike-Sharing Systems for Journey Planning (NG, GM, DR, MT), pp. 703–712.
CIKM-2015-KohjimaMS #matrix: Probabilistic Non-negative Inconsistent-resolution Matrices Factorization (MK, TM, HS), pp. 1855–1858.
CIKM-2015-LiangB #personalisation #rating #recommendation: A Probabilistic Rating Auto-encoder for Personalized Recommender Systems (HL, TB), pp. 1863–1866.
CIKM-2015-LiuZXLL #nondeterminism #set: Finding Probabilistic k-Skyline Sets on Uncertain Data (JL, HZ, LX0, HL, JL), pp. 1511–1520.
CIKM-2015-SangLX #framework #microblog #modelling: A Probabilistic Framework for Temporal User Modeling on Microblogs (JS, DL, CX), pp. 961–970.
ECIR-2015-TsaiKH #approximate #distance #multi: Approximating Weighted Hamming Distance by Probabilistic Selection for Multiple Hash Tables (CYT, YHK, WHH), pp. 123–134.
ICML-2015-BachmanP #collaboration #generative #network: Variational Generative Stochastic Networks with Collaborative Shaping (PB, DP), pp. 1964–1972.
ICML-2015-CsibaQR #adaptation #coordination: Stochastic Dual Coordinate Ascent with Adaptive Probabilities (DC, ZQ, PR), pp. 674–683.
ICML-2015-FilipponeE #linear #process #scalability: Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE) (MF, RE), pp. 1015–1024.
ICML-2015-FouldsKG #framework #modelling #network #programming #topic: Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models (JRF, SHK, LG), pp. 777–786.
ICML-2015-FrostigGKS #algorithm #approximate #empirical #named #performance: Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization (RF, RG, SK, AS), pp. 2540–2548.
ICML-2015-HanMS #scalability: Large-scale log-determinant computation through stochastic Chebyshev expansions (IH, DM, JS), pp. 908–917.
ICML-2015-Hernandez-Lobato #feature model #multi: A Probabilistic Model for Dirty Multi-task Feature Selection (DHL, JMHL, ZG), pp. 1073–1082.
ICML-2015-Hernandez-Lobato15b #learning #network #scalability: Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks (JMHL, RA), pp. 1861–1869.
ICML-2015-HoangHL #big data #framework #modelling #process: A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data (TNH, QMH, BKHL), pp. 569–578.
ICML-2015-HsiehYD #named #parallel: PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent (CJH, HFY, ISD), pp. 2370–2379.
ICML-2015-KomiyamaHN #analysis #multi #problem: Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays (JK, JH, HN), pp. 1152–1161.
ICML-2015-RajkumarGL0 #ranking #set: Ranking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament Solution Sets at the Top (AR, SG, LHL, SA), pp. 665–673.
ICML-2015-SaRO #convergence #matrix #problem: Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix Problems (CDS, CR, KO), pp. 2332–2341.
ICML-2015-ShahKG #algorithm #empirical #process: An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process (AS, DAK, ZG), pp. 1594–1603.
ICML-2015-Shamir #algorithm #convergence #exponential: A Stochastic PCA and SVD Algorithm with an Exponential Convergence Rate (OS), pp. 144–152.
ICML-2015-TheisH #streaming: A trust-region method for stochastic variational inference with applications to streaming data (LT, MDH), pp. 2503–2511.
ICML-2015-WangFS #for free #monte carlo #privacy: Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo (YXW, SEF, AJS), pp. 2493–2502.
ICML-2015-XinW #adaptation #rank: Pushing the Limits of Affine Rank Minimization by Adapting Probabilistic PCA (BX, DPW), pp. 419–427.
ICML-2015-ZhangL #coordination #empirical: Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization (YZ, XL), pp. 353–361.
ICML-2015-ZhaoYZL #adaptation #multi: Adaptive Stochastic Alternating Direction Method of Multipliers (PZ, JY, TZ, PL), pp. 69–77.
ICML-2015-ZhaoZ #optimisation: Stochastic Optimization with Importance Sampling for Regularized Loss Minimization (PZ, TZ), pp. 1–9.
ICML-2015-ZhuE #approach #hybrid #random #using: A Hybrid Approach for Probabilistic Inference using Random Projections (MZ, SE), pp. 2039–2047.
KDD-2015-AhnKLRW #distributed #matrix #scalability #using: Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC (SA, AK, NL, SR, MW), pp. 9–18.
KDD-2015-DuncanE #modelling: Probabilistic Modeling of a Sales Funnel to Prioritize Leads (BAD, CPE), pp. 1751–1758.
KDD-2015-Gomez-Rodriguez #machine learning #modelling #network #problem #research #social: Diffusion in Social and Information Networks: Research Problems, Probabilistic Models and Machine Learning Methods (MGR, LS), pp. 2315–2316.
KDD-2015-HanT #community #network #social: Probabilistic Community and Role Model for Social Networks (YH, JT), pp. 407–416.
KDD-2015-LakretzCFR #modelling #visual notation: Probabilistic Graphical Models of Dyslexia (YL, GC, NF, MRZ), pp. 1919–1928.
KDD-2015-SatoN #online: Stochastic Divergence Minimization for Online Collapsed Variational Bayes Zero Inference of Latent Dirichlet Allocation (IS, HN), pp. 1035–1044.
KDD-2015-TranHXFB #coordination #scalability: Scaling Up Stochastic Dual Coordinate Ascent (KT, SH, LX, TF, MB), pp. 1185–1194.
MLDM-2015-AkbariniaM #streaming: Aggregation-Aware Compression of Probabilistic Streaming Time Series (RA, FM), pp. 232–247.
RecSys-2015-ChaneyBE #network #personalisation #recommendation #social #using: A Probabilistic Model for Using Social Networks in Personalized Item Recommendation (AJBC, DMB, TER), pp. 43–50.
RecSys-2015-KoukiFFEG #flexibility #framework #hybrid #named #recommendation: HyPER: A Flexible and Extensible Probabilistic Framework for Hybrid Recommender Systems (PK, SF, JRF, ME, LG), pp. 99–106.
SEKE-2015-AssuncaoFLSV #automaton #generative #markov #modelling #named #network #predict: SANGE — Stochastic Automata Networks Generator. A tool to efficiently predict events through structured Markovian models (JA, PF, LL, AS, JMV), pp. 581–584.
SEKE-2015-ChenZWLPW #mining #specification: Mining Universal Specification Based on Probabilistic Model (DC, YZ, RW, XL, LP, WW), pp. 471–476.
SIGIR-2015-LiuAH #information retrieval #using: Using Term Location Information to Enhance Probabilistic Information Retrieval (BL, XA, JXH), pp. 883–886.
SIGIR-2015-Paik #information retrieval: A Probabilistic Model for Information Retrieval Based on Maximum Value Distribution (JHP), pp. 585–594.
SIGIR-2015-SchuthBBDGOTVVW #evaluation #multi #online #retrieval: Probabilistic Multileave for Online Retrieval Evaluation (AS, RJB, FB, JvD, CG, HO, CNT, BV, JvdV, RW, DW, MdR), pp. 955–958.
MoDELS-2015-SoltanaSSB #framework #modelling #policy #simulation: A model-based framework for probabilistic simulation of legal policies (GS, NS, MS, LCB), pp. 70–79.
SPLC-2015-BeekLLV #analysis #constraints #modelling #product line #statistics: Statistical analysis of probabilistic models of software product lines with quantitative constraints (MHtB, AL, ALL, AV), pp. 11–15.
OOPSLA-2015-BostonSGC #approximate #flexibility #programming #type inference: Probability type inference for flexible approximate programming (BB, AS, DG, LC), pp. 470–487.
OOPSLA-2015-LeSS #compilation #debugging: Finding deep compiler bugs via guided stochastic program mutation (VL, CS, ZS), pp. 386–399.
PADL-2015-ShterionovJ #implementation #performance #pipes and filters: Implementation and Performance of Probabilistic Inference Pipelines (DSS, GJ), pp. 90–104.
PLDI-2015-NoriORV #performance #source code #synthesis: Efficient synthesis of probabilistic programs (AVN, SO, SKR, DV), pp. 208–217.
POPL-2015-FioritiH #composition #termination: Probabilistic Termination: Soundness, Completeness, and Compositionality (LMFF, HH), pp. 489–501.
POPL-2015-HeGWZ #automaton #composition #concurrent #reasoning: Leveraging Weighted Automata in Compositional Reasoning about Concurrent Probabilistic Systems (FH, XG, BYW, LZ), pp. 503–514.
QAPL-2015-LeeV #bisimulation #branch #congruence: Rooted branching bisimulation as a congruence for probabilistic transition systems (MDL, EPdV), pp. 79–94.
QAPL-2015-RosendahlK #analysis: Probabilistic Output Analysis by Program Manipulation (MR, MHK), pp. 110–124.
ASE-2015-FilieriPY #execution #quantifier #symbolic computation: Quantification of Software Changes through Probabilistic Symbolic Execution (N) (AF, CSP, GY), pp. 703–708.
ASE-2015-GerasimouTC #modelling #re-engineering #search-based #synthesis: Search-Based Synthesis of Probabilistic Models for Quality-of-Service Software Engineering (T) (SG, GT, RC), pp. 319–330.
ESEC-FSE-2015-BorgesFdP #execution #symbolic computation: Iterative distribution-aware sampling for probabilistic symbolic execution (MB, AF, Md, CSP), pp. 866–877.
ESEC-FSE-2015-MorenoCGS #adaptation #approach #model checking #nondeterminism #self: Proactive self-adaptation under uncertainty: a probabilistic model checking approach (GAM, JC, DG, BRS), pp. 1–12.
GTTSE-2015-DwyerFGGPV #program analysis: Probabilistic Program Analysis (MBD, AF, JG, MJG, CSP, WV), pp. 1–25.
ICSE-v1-2015-FilieriGL #adaptation #learning #lightweight #modelling #performance: Lightweight Adaptive Filtering for Efficient Learning and Updating of Probabilistic Models (AF, LG, AL), pp. 200–211.
SAC-2015-CamaraGS0 #adaptation #architecture #game studies #model checking #self: Optimal planning for architecture-based self-adaptation via model checking of stochastic games (JC, DG, BRS, AP), pp. 428–435.
SAC-2015-CruzPQSSOBO #algorithm #game studies #named #using: Amê: an environment to learn and analyze adversarial search algorithms using stochastic card games (ABC, LP, JQ, US, SS, AO, EB, ESO), pp. 208–213.
SAC-2015-HendersonGE #clustering #empirical #named #parametricity #performance: EP-MEANS: an efficient nonparametric clustering of empirical probability distributions (KH, BG, TER), pp. 893–900.
SAC-2015-ShterionovJ #component #pipes and filters: Crucial components in probabilistic inference pipelines (DSS, GJ), pp. 1887–1889.
SAC-2015-StracciaM #concept #estimation #fuzzy #learning #named #owl #using: pFOIL-DL: learning (fuzzy) EL concept descriptions from crisp OWL data using a probabilistic ensemble estimation (US, MM), pp. 345–352.
ASPLOS-2015-MishraZLH #approach #constraints #energy #modelling #performance #visual notation: A Probabilistic Graphical Model-based Approach for Minimizing Energy Under Performance Constraints (NM, HZ, JDL, HH), pp. 267–281.
CASE-2015-ChenW #design #robust: H∞ robust filter design for a class of nonlinear stochastic poisson jump systems (BSC, CFW), pp. 1557–1561.
CASE-2015-XuZLW #order #scheduling #throughput: Stochastic customer order scheduling to maximize throughput (XX, YZ, HL, MW), pp. 665–670.
DAC-2015-ChenH #equivalence #logic: Equivalence among stochastic logic circuits and its application (THC, JPH), p. 6.
DAC-2015-Hayes #challenge: Introduction to stochastic computing and its challenges (JPH), p. 3.
DAC-2015-MundhenkSLFC #analysis #architecture #model checking #security #using: Security analysis of automotive architectures using probabilistic model checking (PM, SS, ML, SAF, SC), p. 6.
DAC-2015-TretterKT #multi: Interleaved multi-bank scratchpad memories: a probabilistic description of access conflicts (AT, PK, LT), p. 6.
DAC-2015-WangSBS #feedback #implementation: Randomness meets feedback: stochastic implementation of logistic map dynamical system (ZW, NS, KB, AS), p. 7.
DATE-2015-AwanoHS #named #performance: ECRIPSE: an efficient method for calculating RTN-induced failure probability of an SRAM cell (HA, MH, TS), pp. 549–554.
DATE-2015-HoqueMS #analysis #approach #maintenance #model checking #reliability #towards: Towards an accurate reliability, availability and maintainability analysis approach for satellite systems based on probabilistic model checking (KAH, OAM, YS), pp. 1635–1640.
DATE-2015-IqtedarHSH #analysis #distributed: Formal probabilistic analysis of distributed dynamic thermal management (SI, OH, MS, JH), pp. 1221–1224.
DATE-2015-JiRML #hardware #implementation #logic #network #using: A hardware implementation of a radial basis function neural network using stochastic logic (YJ, FR, CM, DJL), pp. 880–883.
DATE-2015-LiaperdosAT #detection #estimation #fault #testing: A method for the estimation of defect detection probability of analog/RF defect-oriented tests (JL, AA, YT), pp. 1395–1400.
DATE-2015-MajumderLBP #analysis #architecture #manycore: NoC-enabled multicore architectures for stochastic analysis of biomolecular reactions (TM, XL, PB, PP), pp. 1102–1107.
DATE-2015-ZhaoQ #design #synthesis: A general design of stochastic circuit and its synthesis (ZZ, WQ), pp. 1467–1472.
ESOP-2015-EberlHN #compilation: A Verified Compiler for Probability Density Functions (ME, JH, TN), pp. 80–104.
ESOP-2015-GordonRSBRGT #query #source code #spreadsheet: Probabilistic Programs as Spreadsheet Queries (ADG, CVR, MS, JB, NR, TG, DT), pp. 1–25.
ESOP-2015-TorontoMH #source code: Running Probabilistic Programs Backwards (NT, JM, DVH), pp. 53–79.
FoSSaCS-2015-BizjakB #logic: Step-Indexed Logical Relations for Probability (AB, LB), pp. 279–294.
FoSSaCS-2015-ChadhaSVB #automaton #decidability: Decidable and Expressive Classes of Probabilistic Automata (RC, APS, MV, YB), pp. 200–214.
FoSSaCS-2015-GeblerLT #calculus #composition #metric #process #reasoning: Compositional Metric Reasoning with Probabilistic Process Calculi (DG, KGL, ST), pp. 230–245.
TACAS-2015-BassetKTW #game studies #multi #synthesis: Strategy Synthesis for Stochastic Games with Multiple Long-Run Objectives (NB, MZK, UT, CW), pp. 256–271.
TACAS-2015-ChistikovDM #approximate #estimation #smt #source code: Approximate Counting in SMT and Value Estimation for Probabilistic Programs (DVC, RD, RM), pp. 320–334.
TACAS-2015-KiniV #automaton #ltl: Limit Deterministic and Probabilistic Automata for LTL ∖ GU (DK, MV), pp. 628–642.
TACAS-2015-SoudjaniGA #abstraction #process: FAUST 2 : Formal Abstractions of Uncountable-STate STochastic Processes (SEZS, CG, AA), pp. 272–286.
CAV-2015-DehnertJJCVBKA #named #parametricity #synthesis: PROPhESY: A PRObabilistic ParamEter SYnthesis Tool (CD, SJ, NJ, FC, MV, HB, JPK, EÁ), pp. 214–231.
CSL-2015-KupfermanV #finite #on the: On Relative and Probabilistic Finite Counterability (OK, GV), pp. 175–192.
ICLP-2015-MartinezRIAT #learning #modelling: Learning Probabilistic Action Models from Interpretation Transitions (DM, TR, KI, GA, CT), pp. 114–127.
ICLP-2015-Wang #consistency #nondeterminism #programming #set: Handling Probability and Inconsistency in Answer Set Programming (YW), pp. 319–329.
LICS-2015-AtseriasB: Entailment among Probabilistic Implications (AA, JLB), pp. 621–632.
LICS-2015-BrazdilKKN #behaviour: Long-Run Average Behaviour of Probabilistic Vector Addition Systems (TB, SK, AK, PN), pp. 44–55.
VMCAI-2015-RandourRS #problem: Variations on the Stochastic Shortest Path Problem (MR, JFR, OS), pp. 1–18.
DRR-2014-PuriSH #modelling: Probabilistic modeling of children’s handwriting (MP, SNS, LH), pp. 902103–13.
PODS-2014-FinkO #database #query: A dichotomy for non-repeating queries with negation in probabilistic databases (RF, DO), pp. 144–155.
SIGMOD-2014-ChenW #knowledge base: Knowledge expansion over probabilistic knowledge bases (YC, DZW), pp. 649–660.
SIGMOD-2014-ShenHW #network #web: A probabilistic model for linking named entities in web text with heterogeneous information networks (WS, JH, JW), pp. 1199–1210.
VLDB-2014-YunYHVD #algorithm #distributed #matrix #multi #named: NOMAD: Nonlocking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion (HY, HFY, CJH, SVNV, ISD), pp. 975–986.
ICALP-v1-2014-CanonneR #testing: Testing Probability Distributions Underlying Aggregated Data (CLC, RR), pp. 283–295.
ICALP-v1-2014-EsfandiariHKLMR #online #order #scheduling: Online Stochastic Reordering Buffer Scheduling (HE, MH, MRK, VL, HM, HR), pp. 465–476.
ICALP-v1-2014-MancinskaV #bound: Unbounded Entanglement Can Be Needed to Achieve the Optimal Success Probability (LM, TV), pp. 835–846.
ICALP-v2-2014-JungLGS #first-order #logic: Monodic Fragments of Probabilistic First-Order Logic (JCJ, CL, SG, LS), pp. 256–267.
ICALP-v2-2014-KieferW #automaton #complexity: Stability and Complexity of Minimising Probabilistic Automata (SK, BW), pp. 268–279.
LATA-2014-DingSXHMC #modelling: Stochastic k-Tree Grammar and Its Application in Biomolecular Structure Modeling (LD, AS, XX, XH, RLM, LC), pp. 308–322.
LATA-2014-KleinMBK #automaton #model checking #question: Are Good-for-Games Automata Good for Probabilistic Model Checking? (JK, DM, CB, SK), pp. 453–465.
LATA-2014-LiPT #process #simulation: Probabilistic Simulation for Probabilistic Data-Aware Business Processes (HL, FP, FT), pp. 503–515.
LATA-2014-Weidner #regular expression: Probabilistic ω-Regular Expressions (TW), pp. 588–600.
FM-2014-FengZ #automaton #bisimulation #equivalence: When Equivalence and Bisimulation Join Forces in Probabilistic Automata (YF, LZ), pp. 247–262.
FM-2014-HahnLSTZ #model checking #named: iscasMc: A Web-Based Probabilistic Model Checker (EMH, YL, SS, AT, LZ), pp. 312–317.
IFM-2014-KordyPS #framework #security: A Probabilistic Framework for Security Scenarios with Dependent Actions (BK, MP, PS), pp. 256–271.
CIG-2014-Tsang14a #finite #transducer: Comparing the structure of probabilistic 4- and 8-state finite transducer representations for Prisoner's Dilemma (JT), pp. 1–8.
CHI-2014-SchwarzXMHH #classification #using: Probabilistic palm rejection using spatiotemporal touch features and iterative classification (JS, RX, JM, SEH, CH), pp. 2009–2012.
HIMI-AS-2014-ZhangXCZL #fault #predict: Predictive Probability Model of Pilot Error Based on CREAM (XZ, HX, YC, LZ, GL), pp. 296–304.
CIKM-2014-KangLSSK #coordination #distributed: Data/Feature Distributed Stochastic Coordinate Descent for Logistic Regression (DK, WL, KS, LS, UK), pp. 1269–1278.
CIKM-2014-LiZLW #classification: Probabilistic Classifier Chain Inference via Gibbs Sampling (LL, LZ, GL, HW), pp. 1855–1858.
CIKM-2014-MaSYC #hashtag #modelling #twitter: Tagging Your Tweets: A Probabilistic Modeling of Hashtag Annotation in Twitter (ZM, AS, QY, GC), pp. 999–1008.
CIKM-2014-PfeifferNB #learning #network #using: Active Exploration in Networks: Using Probabilistic Relationships for Learning and Inference (JJPI, JN, PNB), pp. 639–648.
CIKM-2014-TakayamaTIOFC #detection: A Word-Scale Probabilistic Latent Variable Model for Detecting Human Values (YT, YT, EI, DWO, KRF, ASC), pp. 1489–1498.
CIKM-2014-TongZC0 #graph #nondeterminism #performance #scalability: Efficient Probabilistic Supergraph Search Over Large Uncertain Graphs (YT, XZ, CCC, LC), pp. 809–818.
CIKM-2014-YaoRSLF #locality: Exploring Tag-Free RFID-Based Passive Localization and Tracking via Learning-Based Probabilistic Approaches (LY, WR, QZS, XL, NJGF), pp. 1799–1802.
CIKM-2014-YuSYL #distributed #matrix: Distributed Stochastic ADMM for Matrix Factorization (ZQY, XJS, LY, WJL), pp. 1259–1268.
CIKM-2014-Zhang0T #collaboration #framework #named #query: MaC: A Probabilistic Framework for Query Answering with Machine-Crowd Collaboration (CJZ, LC, YT), pp. 11–20.
CIKM-2014-ZhaoCN #approach #data type: Truth Discovery in Data Streams: A Single-Pass Probabilistic Approach (ZZ, JC, WN), pp. 1589–1598.
ECIR-2014-HoulsbyC #scalability: A Scalable Gibbs Sampler for Probabilistic Entity Linking (NH, MC), pp. 335–346.
ICML-c1-2014-AzadiS #multi #towards: Towards an optimal stochastic alternating direction method of multipliers (SA, SS), pp. 620–628.
ICML-c1-2014-Shalev-Shwartz0 #coordination: Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization (SSS, TZ), pp. 64–72.
ICML-c1-2014-Suzuki #coordination #multi: Stochastic Dual Coordinate Ascent with Alternating Direction Method of Multipliers (TS), pp. 736–744.
ICML-c1-2014-ZhongK #multi #performance: Fast Stochastic Alternating Direction Method of Multipliers (WZ, JTYK), pp. 46–54.
ICML-c1-2014-ZhouT #generative #network #predict: Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction (JZ, OGT), pp. 745–753.
ICML-c2-2014-0001NKA #estimation: GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare (AA, HN, SK, SA), pp. 1989–1997.
ICML-c2-2014-AhnSW #distributed: Distributed Stochastic Gradient MCMC (SA, BS, MW), pp. 1044–1052.
ICML-c2-2014-AzarLB #correlation #feedback #online #optimisation: Online Stochastic Optimization under Correlated Bandit Feedback (MGA, AL, EB), pp. 1557–1565.
ICML-c2-2014-BalleHP #comparison #empirical #learning: Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison (BB, WLH, JP), pp. 1386–1394.
ICML-c2-2014-BengioLAY #generative #network: Deep Generative Stochastic Networks Trainable by Backprop (YB, EL, GA, JY), pp. 226–234.
ICML-c2-2014-CelikkayaS #markov #process: Deterministic Anytime Inference for Stochastic Continuous-Time Markov Processes (EBC, CRS), pp. 1962–1970.
ICML-c2-2014-ChenFG #monte carlo: Stochastic Gradient Hamiltonian Monte Carlo (TC, EBF, CG), pp. 1683–1691.
ICML-c2-2014-Hernandez-LobatoHG #matrix #modelling #scalability: Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices (JMHL, NH, ZG), pp. 379–387.
ICML-c2-2014-Hernandez-LobatoHG14a #matrix: Probabilistic Matrix Factorization with Non-random Missing Data (JMHL, NH, ZG), pp. 1512–1520.
ICML-c2-2014-JohnsonW #modelling: Stochastic Variational Inference for Bayesian Time Series Models (MJ, ASW), pp. 1854–1862.
ICML-c2-2014-KusnerTWA: Stochastic Neighbor Compression (MJK, ST, KQW, KA), pp. 622–630.
ICML-c2-2014-LiuWRBS #algorithm #coordination #parallel: An Asynchronous Parallel Stochastic Coordinate Descent Algorithm (JL, SW, CR, VB, SS), pp. 469–477.
ICML-c2-2014-MukutaH #analysis #canonical #correlation: Probabilistic Partial Canonical Correlation Analysis (YM, TH), pp. 1449–1457.
ICML-c2-2014-PaigeW #compilation #programming language: A Compilation Target for Probabilistic Programming Languages (BP, FW), pp. 1935–1943.
ICML-c2-2014-RezendeMW #approximate #generative #modelling: Stochastic Backpropagation and Approximate Inference in Deep Generative Models (DJR, SM, DW), pp. 1278–1286.
ICML-c2-2014-SatoN #analysis #approximate #equation #process #using: Approximation Analysis of Stochastic Gradient Langevin Dynamics by using Fokker-Planck Equation and Ito Process (IS, HN), pp. 982–990.
ICML-c2-2014-SeldinS #algorithm: One Practical Algorithm for Both Stochastic and Adversarial Bandits (YS, AS), pp. 1287–1295.
ICML-c2-2014-Sohl-DicksteinPG #optimisation #performance #scalability: Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods (JSD, BP, SG), pp. 604–612.
ICML-c2-2014-TitsiasL: Doubly Stochastic Variational Bayes for non-Conjugate Inference (MKT, MLG), pp. 1971–1979.
ICML-c2-2014-ToulisAR #analysis #linear #modelling #statistics: Statistical analysis of stochastic gradient methods for generalized linear models (PT, EA, JR), pp. 667–675.
ICPR-2014-AghdamPS #adaptation #segmentation: Adaptive Probabilistic Thresholding Method for Accurate Breast Region Segmentation in Mammograms (HHA, DP, AS), pp. 3357–3362.
ICPR-2014-AliNB #classification #constraints #image #scalability: Boosting Stochastic Newton with Entropy Constraint for Large-Scale Image Classification (WBHA, RN, MB), pp. 232–237.
ICPR-2014-CorringR #representation #set: Shape from Phase: An Integrated Level Set and Probability Density Shape Representation (JC, AR), pp. 46–51.
ICPR-2014-HuML #composition: Dynamic Task Decomposition for Probabilistic Tracking in Complex Scenes (TH, SM, OL), pp. 4134–4139.
ICPR-2014-LiDXWP #classification #image: Local Label Probability Propagation for Hyperspectral Image Classification (HL, JD, SX, LW, CP), pp. 4251–4256.
ICPR-2014-Martinez-VargasHAAC #component #constraints #recursion: Recursive Separation of Stationary Components by Subspace Projection and Stochastic Constraints (JDMV, CCH, AMÁM, CDAM, GCD), pp. 3469–3474.
ICPR-2014-PakKA #detection: Improvement of Benign and Malignant Probability Detection Based on Non-subsample Contourlet Transform and Super-resolution (FP, HRK, AA), pp. 895–899.
ICPR-2014-QureshiHA #using: A Probabilistic Model for the Optimal Configuration of Retinal Junctions Using Theoretically Proven Features (TAQ, AH, BAD), pp. 3304–3309.
KDD-2014-0001GHHLMSSZ #approach: Knowledge vault: a web-scale approach to probabilistic knowledge fusion (XD, EG, GH, WH, NL, KM, TS, SS, WZ), pp. 601–610.
KDD-2014-GunnemannGF #detection #evolution #rating #robust: Detecting anomalies in dynamic rating data: a robust probabilistic model for rating evolution (SG, NG, CF), pp. 841–850.
KDD-2014-KurashimaITS #network #visualisation: Probabilistic latent network visualization: inferring and embedding diffusion networks (TK, TI, NT, HS), pp. 1236–1245.
KDD-2014-LiuGXXGP #modelling #process #workflow: Proactive workflow modeling by stochastic processes with application to healthcare operation and management (CL, YG, HX, KX, WG, MP), pp. 1593–1602.
KDD-2014-LiZCS #optimisation #performance: Efficient mini-batch training for stochastic optimization (ML, TZ, YC, AJS), pp. 661–670.
KDD-2014-TangL #scalability: Scalable histograms on large probabilistic data (MT, FL), pp. 631–640.
KDD-2014-ZhangCSWZ #network #set #social: Minimizing seed set selection with probabilistic coverage guarantee in a social network (PZ, WC, XS, YW, JZ), pp. 1306–1315.
KR-2014-KisaBCD #diagrams: Probabilistic Sentential Decision Diagrams (DK, GVdB, AC, AD).
KR-2014-Potyka #consistency #linear #logic #nondeterminism #source code: Linear Programs for Measuring Inconsistency in Probabilistic Logics (NP).
RecSys-2014-AdamopoulosT14a #bias #collaboration #on the #recommendation: On over-specialization and concentration bias of recommendations: probabilistic neighborhood selection in collaborative filtering systems (PA, AT), pp. 153–160.
RecSys-2014-PetroniQ #clustering #distributed #graph #matrix #named: GASGD: stochastic gradient descent for distributed asynchronous matrix completion via graph partitioning (FP, LQ), pp. 241–248.
SEKE-2014-FernandesALG #modelling #process #reduction: A Dimensionality Reduction Process to Forecast Events through Stochastic Models (PF, JA, LL, SG), pp. 534–539.
SEKE-2014-ZhouWLZ #correctness #empirical #test coverage #testing: An Empirical Study on the Test Adequacy Criterion Based on Coincidental Correctness Probability (XZ, LW, XL, JZ), pp. 632–635.
SIGIR-2014-CaiLR #documentation #matrix #personalisation #ranking: Personalized document re-ranking based on Bayesian probabilistic matrix factorization (FC, SL, MdR), pp. 835–838.
SIGIR-2014-LiuL #learning #segmentation #word: Probabilistic ensemble learning for vietnamese word segmentation (WL, LL), pp. 931–934.
SIGIR-2014-LuoZY #game studies: Win-win search: dual-agent stochastic game in session search (JL, SZ, HY), pp. 587–596.
SIGIR-2014-ParkS #detection #higher-order #modelling: Second order probabilistic models for within-document novelty detection in academic articles (LAFP, SS), pp. 1103–1106.
SIGIR-2014-YaoZJBCSY #modelling #topic: Probabilistic text modeling with orthogonalized topics (EY, GZ, OJ, SB, KC, ZS, YY), pp. 907–910.
SIGIR-2014-ZhaoH #information retrieval #proximity: An enhanced context-sensitive proximity model for probabilistic information retrieval (JZ, JXH), pp. 1131–1134.
OOPSLA-2014-ZhaoWZDSSW #automaton #predict #sequence: Call sequence prediction through probabilistic calling automata (ZZ, BW, MZ, YD, JS, XS, YW), pp. 745–762.
PLDI-2014-BorgesFdPV #analysis #composition #quantifier: Compositional solution space quantification for probabilistic software analysis (MB, AF, Md, CSP, WV), p. 15.
PLDI-2014-HurNRS #slicing #source code: Slicing probabilistic programs (CKH, AVN, SKR, SS), p. 16.
PLDI-2014-SampsonPMMGC #verification: Expressing and verifying probabilistic assertions (AS, PP, TM, KSM, DG, LC), p. 14.
PLDI-2014-Schkufza0A #float #optimisation #precise #source code: Stochastic optimization of floating-point programs with tunable precision (ES, RS, AA), p. 9.
POPL-2014-BartheFGSSB #encryption #implementation #relational #verification: Probabilistic relational verification for cryptographic implementations (GB, CF, BG, PYS, NS, SZB), pp. 193–206.
POPL-2014-EhrhardTP: Probabilistic coherence spaces are fully abstract for probabilistic PCF (TE, CT, MP), pp. 309–320.
POPL-2014-GordonGRRBG #named #programming language: Tabular: a schema-driven probabilistic programming language (ADG, TG, NR, CVR, JB, JG), pp. 321–334.
POPL-2014-LagoSA #functional #higher-order #induction #on the #source code: On coinductive equivalences for higher-order probabilistic functional programs (UDL, DS, MA), pp. 297–308.
QAPL-2014-Feng #distributed #hybrid #modelling #using: Patch-based Hybrid Modelling of Spatially Distributed Systems by Using Stochastic HYPE — ZebraNet as an Example (CF0), pp. 64–77.
SAS-2014-ChakarovS #fixpoint #invariant: Expectation Invariants for Probabilistic Program Loops as Fixed Points (AC, SS), pp. 85–100.
ASE-2014-LuckowPDFV #approximate #execution #nondeterminism #source code #symbolic computation: Exact and approximate probabilistic symbolic execution for nondeterministic programs (KSL, CSP, MBD, AF, WV), pp. 575–586.
ICSE-2014-SuR #analysis #empirical #parametricity: Perturbation analysis of stochastic systems with empirical distribution parameters (GS, DSR), pp. 311–321.
SAC-2014-BelbachirBM #modelling: Probabilistic opinion models based on subjective sources (FB, MB, MMSM), pp. 925–926.
CASE-2014-FrigerioM #energy #policy: Energy saving policies for a machine tool with warm-up, stochastic arrivals and buffer information (NF, AM), pp. 646–651.
CASE-2014-HuangJXGX #energy #nondeterminism #scheduling: EV charging load scheduling following uncertain renewable energy supply by stochastic matching (QH, QSJ, LX, XG, XX), pp. 137–142.
CASE-2014-HuangL #multi: Stochastic chiller sequencing control for multiple-chiller plants (GH, ZL), pp. 1085–1090.
CASE-2014-LiLT #petri net #process #scheduling: A color petri net based scheduling model for remanufacturing system with stochastic process routing (LL, CL, YT), pp. 474–479.
CASE-2014-LongLXJ #distributed: A scenario-based distributed stochastic MPC for building temperature regulation (YL, SL, LX, KHJ), pp. 1091–1096.
CASE-2014-XuLYM #integer #programming: A mixed integer programming model for Bed planning considering stochastic length of stay (LX, NL, XY, FM), pp. 1069–1074.
CASE-2014-YuanLJ #health #problem #scheduling: Home health care crew scheduling and routing problem with stochastic service times (BY, RL, ZJ), pp. 564–569.
DAC-2014-LiangC #analysis #clustering #named #network #reduction #scalability #smarttech: ClusRed: Clustering and Network Reduction Based Probabilistic Optimal Power Flow Analysis for Large-Scale Smart Grids (YL, DC), p. 6.
DAC-2014-YounGK #debugging #locality #statistics: Probabilistic Bug Localization via Statistical Inference based on Partially Observed Data (SY, CG, JK), p. 6.
DATE-2014-AlaghiH #performance #using: Fast and accurate computation using stochastic circuits (AA, JPH), pp. 1–4.
DATE-2014-AltmeyerD #analysis #correctness #on the #precise: On the correctness, optimality and precision of Static Probabilistic Timing Analysis (SA, RID), pp. 1–6.
DATE-2014-HaddadTBF #independence #modelling #on the: On the assumption of mutual independence of jitter realizations in P-TRNG stochastic models (PH, YT, FB, VF), pp. 1–6.
DATE-2014-LangeSJHLS #correlation #modelling #parametricity #standard: Probabilistic standard cell modeling considering non-Gaussian parameters and correlations (AL, CS, RJ, JH, IL, US), pp. 1–4.
DATE-2014-SarafBLR #using: IIR filters using stochastic arithmetic (NS, KB, DJL, MDR), pp. 1–6.
DATE-2014-ShenCQ #mobile: Battery aware stochastic QoS boosting in mobile computing devices (HS, QC, QQ), pp. 1–4.
DATE-2014-ZhangB #analysis: Stochastic analysis of Bubble Razor (GZ, PAB), pp. 1–6.
ESOP-2014-CrubilleL #bisimulation #call-by #on the #λ-calculus: On Probabilistic Applicative Bisimulation and Call-by-Value λ-Calculi (RC, UDL), pp. 209–228.
FASE-2014-BaierDKDKMW #model checking #multi #reasoning #standard: Probabilistic Model Checking and Non-standard Multi-objective Reasoning (CB, CD, SK, MD, JK, SM, SW), pp. 1–16.
FoSSaCS-2014-BertrandFHHH: Active Diagnosis for Probabilistic Systems (NB, EF, SH, SH, LH), pp. 29–42.
FoSSaCS-2014-BonnetKL #analysis #parallel #process: Analysis of Probabilistic Basic Parallel Processes (RB, SK, AWL), pp. 43–57.
FoSSaCS-2014-Chatterjee0GO #game studies: Perfect-Information Stochastic Mean-Payoff Parity Games (KC, LD, HG, YO), pp. 210–225.
FoSSaCS-2014-Chatterjee0NV #complexity #game studies: The Complexity of Partial-Observation Stochastic Parity Games with Finite-Memory Strategies (KC, LD, SN, MYV), pp. 242–257.
FoSSaCS-2014-DArgenioGL #axiom #bisimulation #metric: Axiomatizing Bisimulation Equivalences and Metrics from Probabilistic SOS Rules (PRD, DG, MDL), pp. 289–303.
FoSSaCS-2014-Fu #bound #markov #process #reachability: Maximal Cost-Bounded Reachability Probability on Continuous-Time Markov Decision Processes (HF), pp. 73–87.
TACAS-2014-DragerFKPU #synthesis: Permissive Controller Synthesis for Probabilistic Systems (KD, VF, MZK, DP, MU), pp. 531–546.
TACAS-2014-SoudjaniA #approximate #markov #precise #process: Precise Approximations of the Probability Distribution of a Markov Process in Time: An Application to Probabilistic Invariance (SEZS, AA), pp. 547–561.
CAV-2014-ChatterjeeCD #analysis: CEGAR for Qualitative Analysis of Probabilistic Systems (KC, MC, PD), pp. 473–490.
ICLP-J-2014-BellodiLRCZ #logic programming: Lifted Variable Elimination for Probabilistic Logic Programming (EB, EL, FR, VSC, RZ), pp. 681–695.
ICST-2014-PouldingW #automation: Adding Contextual Guidance to the Automated Search for Probabilistic Test Profiles (SMP, HW), pp. 293–302.
LICS-CSL-2014-BaierDK #analysis #model checking #trade-off: Trade-off analysis meets probabilistic model checking (CB, CD, SK), p. 10.
LICS-CSL-2014-BilokonE #approach #process: A domain-theoretic approach to Brownian motion and general continuous stochastic processes (PB, AE), p. 10.
LICS-CSL-2014-BrazdilKKNK #automaton #multi: Zero-reachability in probabilistic multi-counter automata (TB, SK, AK, PN, JPK), p. 10.
VMCAI-2014-KiniV #automaton #ltl #safety #specification: Probabilistic Automata for Safety LTL Specifications (DK, MV), pp. 118–136.
DocEng-2013-AhmadullinD #composition: Hierarchical probabilistic model for news composition (IA, NDV), pp. 141–150.
ICDAR-2013-AlaeiDG #detection #representation #using: Logo Detection Using Painting Based Representation and Probability Features (AA, MD, NG), pp. 1235–1239.
ICDAR-2013-FeildLS #recognition #using: Using a Probabilistic Syllable Model to Improve Scene Text Recognition (JLF, EGLM, DAS), pp. 897–901.
ICDAR-2013-RoyG #documentation #forensics #re-engineering: A Probabilistic Model for Reconstruction of Torn Forensic Documents (AR, UG), pp. 494–498.
JCDL-2013-TuarobPG #automation #metadata #modelling #recommendation #topic #using: Automatic tag recommendation for metadata annotation using probabilistic topic modeling (ST, LCP, CLG), pp. 239–248.
VLDB-2013-0007TR #effectiveness #graph #keyword #performance #query: Probabilistic Query Rewriting for Efficient and Effective Keyword Search on Graph Data (LZ, TT, AR), pp. 1642–1653.
VLDB-2013-DuanZCG #approach #database #keyword: Supporting Keyword Search in Product Database: A Probabilistic Approach (HD, CZ, JC, AG), pp. 1786–1797.
VLDB-2013-MottinMRDPV #framework #optimisation #problem: A Probabilistic Optimization Framework for the Empty-Answer Problem (DM, AM, SBR, GD, TP, YV), pp. 1762–1773.
VLDB-2013-ZhouTWN #2d #learning #named #predict: R2-D2: a System to Support Probabilistic Path Prediction in Dynamic Environments via “Semi-Lazy” Learning (JZ, AKHT, WW, WSN), pp. 1366–1369.
VLDB-2014-NiedermayerZERM0K13 #nearest neighbour #nondeterminism #query: Probabilistic Nearest Neighbor Queries on Uncertain Moving Object Trajectories (JN, AZ, TE, MR, NM, LC, HPK), pp. 205–216.
ICSM-2013-RosePFP #framework #platform #scalability #search-based #testing #towards: Towards a Scalable Cloud Platform for Search-Based Probabilistic Testing (LMR, SMP, RF, RFP), pp. 480–483.
DLT-2013-Regnault #automaton #proving: Proof of a Phase Transition in Probabilistic Cellular Automata (DR), pp. 433–444.
ICALP-v1-2013-BorosEGM #algorithm #game studies #pseudo #random: A Pseudo-Polynomial Algorithm for Mean Payoff Stochastic Games with Perfect Information and a Few Random Positions (EB, KME, VG, KM), pp. 220–231.
ICALP-v2-2013-BartheO #composition #difference #logic #privacy #relational #source code #theorem: Beyond Differential Privacy: Composition Theorems and Relational Logic for f-divergences between Probabilistic Programs (GB, FO), pp. 49–60.
ICALP-v2-2013-Basset #automaton #process: A Maximal Entropy Stochastic Process for a Timed Automaton, (NB), pp. 61–73.
ICALP-v2-2013-EtessamiSY #context-free grammar #regular expression: Stochastic Context-Free Grammars, Regular Languages, and Newton’s Method (KE, AS, MY), pp. 199–211.
LATA-2013-Etessami #algorithm #infinity #recursion #verification: Algorithms for Analyzing and Verifying Infinite-State Recursive Probabilistic Systems (KE), p. 12.
GT-VMT-2013-Giese #behaviour #graph transformation: Invited Talk: Extensions of Graph Transformation Systems for Timed, Continuous, and Probabilistic Behavior (HG).
HCI-III-2013-ShinKS #image #retrieval #using: Affect-Based Retrieval of Landscape Images Using Probabilistic Affective Model (YS, EYK, TES), pp. 362–371.
HCI-UC-2013-KellenCF #diagrams #performance #problem: Improving User Performance in Conditional Probability Problems with Computer-Generated Diagrams (VK, SSC, XF), pp. 183–192.
CIKM-2013-KimNC #approach #modelling #social #social media: Modeling dynamics of meta-populations with a probabilistic approach: global diffusion in social media (MK, DN, PC), pp. 489–498.
CIKM-2013-Lian0 #database #nondeterminism #query: Causality and responsibility: probabilistic queries revisited in uncertain databases (XL, LC), pp. 349–358.
CIKM-2013-LiWZWW #scalability #similarity: Computing term similarity by large probabilistic isA knowledge (PPL, HW, KQZ, ZW, XW), pp. 1401–1410.
CIKM-2013-ShirakawaNHN #metric #semantics #similarity #using #wiki: Probabilistic semantic similarity measurements for noisy short texts using Wikipedia entities (MS, KN, TH, SN), pp. 903–908.
CIKM-2013-ZhangDDC #network #social: Probabilistic solutions of influence propagation on social networks (MZ, CD, CHQD, EC), pp. 429–438.
ECIR-2013-MoensV #information retrieval #modelling #topic: Monolingual and Cross-Lingual Probabilistic Topic Models and Their Applications in Information Retrieval (MFM, IV), pp. 874–877.
ECIR-2013-VulicM #framework #modelling #topic: A Unified Framework for Monolingual and Cross-Lingual Relevance Modeling Based on Probabilistic Topic Models (IV, MFM), pp. 98–109.
ICML-c1-2013-HeaukulaniG #modelling #network #social: Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks (CH, ZG), pp. 275–283.
ICML-c1-2013-Hennig #optimisation #performance: Fast Probabilistic Optimization from Noisy Gradients (PH), pp. 62–70.
ICML-c1-2013-OuyangHTG #multi: Stochastic Alternating Direction Method of Multipliers (HO, NH, LT, AGG), pp. 80–88.
ICML-c1-2013-RamdasS #optimisation: Optimal rates for stochastic convex optimization under Tsybakov noise condition (AR, AS), pp. 365–373.
ICML-c1-2013-Shamir0 #convergence #optimisation: Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes (OS, TZ), pp. 71–79.
ICML-c1-2013-XiaoG #adaptation #sequence: Domain Adaptation for Sequence Labeling Tasks with a Probabilistic Language Adaptation Model (MX, YG), pp. 293–301.
ICML-c2-2013-RanganathWBX #adaptation #learning: An Adaptive Learning Rate for Stochastic Variational Inference (RR, CW, DMB, EPX), pp. 298–306.
ICML-c2-2013-ValkoCM #optimisation: Stochastic Simultaneous Optimistic Optimization (MV, AC, RM), pp. 19–27.
ICML-c3-2013-SodomkaHLG #game studies #learning #named: Coco-Q: Learning in Stochastic Games with Side Payments (ES, EH, MLL, AG), pp. 1471–1479.
ICML-c3-2013-SzorenyiBHOJK #algorithm #distributed: Gossip-based distributed stochastic bandit algorithms (BS, RBF, IH, RO, MJ, BK), pp. 19–27.
ICML-c3-2013-TarlowSCSZ #learning: Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning (DT, KS, LC, IS, RSZ), pp. 199–207.
ICML-c3-2013-TeschSC #optimisation: Expensive Function Optimization with Stochastic Binary Outcomes (MT, JGS, HC), pp. 1283–1291.
ICML-c3-2013-ZhangYJH #optimisation: O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions (LZ, TY, RJ, XH), pp. 1121–1129.
KDD-2013-BahadoriLX #learning #performance #process: Fast structure learning in generalized stochastic processes with latent factors (MTB, YL, EPX), pp. 284–292.
KDD-2013-ChenXJ #modelling #multi #sequence: Multi-space probabilistic sequence modeling (SC, JX, TJ), pp. 865–873.
KDD-2013-FouldsBDSW: Stochastic collapsed variational Bayesian inference for latent Dirichlet allocation (JRF, LB, CD, PS, MW), pp. 446–454.
KDD-2013-LiuCZ #approach #performance: Summarizing probabilistic frequent patterns: a fast approach (CL, LC, CZ), pp. 527–535.
KDD-2013-Mu0ZT #problem #scalability: Constrained stochastic gradient descent for large-scale least squares problem (YM, WD, TZ, DT), pp. 883–891.
KDD-2013-SongZSHUS #modelling #reasoning #scalability: Modeling and probabilistic reasoning of population evacuation during large-scale disaster (XS, QZ, YS, TH, SU, RS), pp. 1231–1239.
KDD-2013-WangZR #comprehension #evolution #generative #research: Understanding evolution of research themes: a probabilistic generative model for citations (XW, CZ, DR), pp. 1115–1123.
KDD-2013-YangHLC #network #online #social: Maximizing acceptance probability for active friending in online social networks (DNY, HJH, WCL, WC), pp. 713–721.
KDD-2013-ZhouTWN #approach #predict: A “semi-lazy” approach to probabilistic path prediction (JZ, AKHT, WW, WSN), pp. 748–756.
MLDM-2013-WilliamsHFR #classification #distance #evaluation: Area under the Distance Threshold Curve as an Evaluation Measure for Probabilistic Classifiers (SW, MH, JDF, DSR), pp. 644–657.
RecSys-2013-BelloginPC #collaboration: Probabilistic collaborative filtering with negative cross entropy (AB, JP, PC), pp. 387–390.
SIGIR-2013-AbdulahhadCB #nondeterminism #question: Is uncertain logical-matching equivalent to conditional probability? (KA, JPC, CB), pp. 825–828.
SIGIR-2013-AnH #analysis #information retrieval #semantics: Boosting novelty for biomedical information retrieval through probabilistic latent semantic analysis (XA, JXH), pp. 829–832.
PLDI-2013-SankaranarayananCG #source code #static analysis: Static analysis for probabilistic programs: inferring whole program properties from finitely many paths (SS, AC, SG), pp. 447–458.
POPL-2013-Goodman #programming: The principles and practice of probabilistic programming (NDG), pp. 399–402.
QAPL-2013-BernardoNL #behaviour #nondeterminism #process: The Spectrum of Strong Behavioral Equivalences for Nondeterministic and Probabilistic Processes (MB, RDN, ML), pp. 81–96.
QAPL-2013-BertrandS #automaton #game studies #infinity: Solving Stochastic Büchi Games on Infinite Decisive Arenas (NB, PS), pp. 116–131.
QAPL-2013-HanKKG #specification: Modal Specifications for Probabilistic Timed Systems (TH, CK, MZK, HG), pp. 66–80.
QAPL-2013-McIverRS #algebra #concurrent: Probabilistic Concurrent Kleene Algebra (AM, TMR, GS), pp. 97–115.
SAC-2013-BifetPRH #adaptation #classification #data type #performance: Efficient data stream classification via probabilistic adaptive windows (AB, BP, JR, GH), pp. 801–806.
SAC-2013-BlancoMLJ #approach: A Kalman filter based approach to probabilistic gas distribution mapping (JLB, JGM, AJL, JGJ), pp. 217–222.
SAC-2013-MarianiO: Probabilistic embedding: experiments with tuple-based probabilistic languages (SM, AO), pp. 1380–1382.
SAC-2013-Markovski #communication #coordination #process #reliability: Reliable supervisory coordination of stochastic communicating processes with data (JM), pp. 1347–1354.
ASPLOS-2013-Schkufza0A: Stochastic superoptimization (ES, RS, AA), pp. 305–316.
CASE-2013-BentahaBD #composition: A decomposition method for stochastic partial disassembly line balancing with profit maximization (MLB, OB, AD), pp. 404–409.
CASE-2013-ChenK #distributed: Decentralized failure diagnosis of stochastic discrete event systems (JC, RK), pp. 1083–1088.
CASE-2013-GaoZS #evaluation: Evaluation of improvement probability for IMRT plans (SG, XZ, LS), pp. 474–479.
DAC-2013-AlaghiLH #realtime: Stochastic circuits for real-time image-processing applications (AA, CL, JPH), p. 6.
DAC-2013-AxerE #fault #scheduling: Stochastic response-time guarantee for non-preemptive, fixed-priority scheduling under errors (PA, RE), p. 7.
DATE-2013-GielenM #modelling #simulation: Stochastic degradation modeling and simulation for analog integrated circuits in nanometer CMOS (GGEG, EM), pp. 326–331.
DATE-2013-KosmidisCQABC #analysis #design: Probabilistic timing analysis on conventional cache designs (LK, CC, EQ, JA, EDB, FJC), pp. 603–606.
DATE-2013-ZhaoLBT #detection #manycore #runtime: Run-time probabilistic detection of miscalibrated thermal sensors in many-core systems (JZ, S(L, WB, RT), pp. 1395–1398.
PDP-2013-AldinucciDTCT #biology #evolution #parallel: Parallel Stochastic Simulators in System Biology: The Evolution of the Species (MA, MD, FT, MC, MT), pp. 410–419.
PDP-2013-MoscaMMCD #biology #implementation #modelling #parallel: A Parallel Implementation of the Stau-DPP Stochastic Simulator for the Modelling of Biological Systems (EM, IM, LM, AC, DD), pp. 427–431.
ESOP-2013-KatoenP #concurrent #implementation #modelling: Taming Confusion for Modeling and Implementing Probabilistic Concurrent Systems (JPK, DP), pp. 411–430.
FASE-2013-BapodraH #abstraction #graph transformation: Abstraction and Training of Stochastic Graph Transformation Systems (MB, RH), pp. 312–326.
FASE-2013-BouchouchaSL #behaviour #comprehension #modelling #towards #using: Towards Understanding the Behavior of Classes Using Probabilistic Models of Program Inputs (AB, HAS, PL), pp. 99–113.
FoSSaCS-2013-MioS #composition #concurrent #process #proving #verification: A Proof System for Compositional Verification of Probabilistic Concurrent Processes (MM, AS), pp. 161–176.
STOC-2013-LiY #approximate #combinator #optimisation: Stochastic combinatorial optimization via poisson approximation (JL, WY), pp. 971–980.
TACAS-2013-BhatBGR #functional #source code: Deriving Probability Density Functions from Probabilistic Functional Programs (SB, JB, ADG, CVR), pp. 508–522.
TACAS-2013-ChenFKPS #game studies #model checking #multi #named: PRISM-games: A Model Checker for Stochastic Multi-Player Games (TC, VF, MZK, DP, AS), pp. 185–191.
TACAS-2013-EisentrautHST0 #automaton: The Quest for Minimal Quotients for Probabilistic Automata (CE, HH, JS, AT, LZ), pp. 16–31.
TACAS-2013-KempfBM #nondeterminism #scheduling: As Soon as Probable: Optimal Scheduling under Stochastic Uncertainty (JFK, MB, OM), pp. 385–400.
CAV-2013-BrimCDS #model checking #parametricity #using: Exploring Parameter Space of Stochastic Biochemical Systems Using Quantitative Model Checking (LB, MC, SD, DS), pp. 107–123.
CAV-2013-ChakarovS #program analysis: Probabilistic Program Analysis with Martingales (AC, SS), pp. 511–526.
CAV-2013-ChatterjeeGK #automaton #ltl #model checking #synthesis: Automata with Generalized Rabin Pairs for Probabilistic Model Checking and LTL Synthesis (KC, AG, JK), pp. 559–575.
CAV-2013-StewartEY #automaton #bound #model checking #polynomial: Upper Bounds for Newton’s Method on Monotone Polynomial Systems, and P-Time Model Checking of Probabilistic One-Counter Automata (AS, KE, MY), pp. 495–510.
ICLP-J-2013-SneyersSF #reasoning: Probabilistic legal reasoning in CHRiSM (JS, DDS, TWF), pp. 769–781.
LICS-2013-Lynch #automaton: Timed and Probabilistic I/O Automata (NAL), p. 12.
LICS-2013-NainV #game studies: Solving Partial-Information Stochastic Parity Games (SN, MYV), pp. 341–348.
SAT-2013-FingerLGS #constraints #satisfiability #using: Solutions for Hard and Soft Constraints Using Optimized Probabilistic Satisfiability (MF, RL, CPG, BS), pp. 233–249.
CBSE-2012-BenesBCO #analysis #component #development #model checking #reliability: Reliability analysis in component-based development via probabilistic model checking (NB, BB, IC, RO), pp. 83–92.
SIGMOD-2012-LiG #online #sequence: Online windowed subsequence matching over probabilistic sequences (ZL, TG), pp. 277–288.
SIGMOD-2012-RekatsinasDG #database: Local structure and determinism in probabilistic databases (TR, AD, LG), pp. 373–384.
SIGMOD-2012-WuLWZ #comprehension #named #taxonomy: Probase: a probabilistic taxonomy for text understanding (WW, HL, HW, KQZ), pp. 481–492.
VLDB-2012-CautisK #complexity #query #using #xml: Answering Queries using Views over Probabilistic XML: Complexity and Tractability (BC, EK), pp. 1148–1159.
VLDB-2012-FinkHO #compilation #database: Aggregation in Probabilistic Databases via Knowledge Compilation (RF, LH, DO), pp. 490–501.
VLDB-2012-HalimIKY #adaptation #database #in memory #robust #towards: Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores (FH, SI, PK, RHCY), pp. 502–513.
VLDB-2012-JhaS #database: Probabilistic Databases with MarkoViews (AKJ, DS), pp. 1160–1171.
VLDB-2012-YuanWCW #database #graph #performance #scalability #similarity: Efficient Subgraph Similarity Search on Large Probabilistic Graph Databases (YY, GW, LC, HW), pp. 800–811.
ITiCSE-2012-KortsartsK #component #programming: Enriching introductory programming courses with non-intuitive probability experiments component (YK, YK), pp. 128–131.
CIAA-2012-Oliveira #algebra #automaton #linear: Typed Linear Algebra for Weigthed (Probabilistic) Automata (JNO), pp. 52–65.
ICALP-v1-2012-CostelloTT: Stochastic Matching with Commitment (KPC, PT, PT), pp. 822–833.
ICALP-v1-2012-EtessamiSY #algorithm #branch #equation #markov #polynomial #process: Polynomial Time Algorithms for Branching Markov Decision Processes and Probabilistic Min(Max) Polynomial Bellman Equations (KE, AS, MY), pp. 314–326.
ICALP-v1-2012-GortzNS: Stochastic Vehicle Routing with Recourse (ILG, VN, RS), pp. 411–423.
IFM-2012-KazemeyniJOB #analysis #modelling #network: MULE-Based Wireless Sensor Networks: Probabilistic Modeling and Quantitative Analysis (FK, EBJ, OO, IB), pp. 143–157.
IFM-2012-TarasyukTL #formal method #modelling #verification: Formal Modelling and Verification of Service-Oriented Systems in Probabilistic Event-B (AT, ET, LL), pp. 237–252.
SEFM-2012-OuchaniMD #abstraction #diagrams #performance #process: Efficient Probabilistic Abstraction for SysML Activity Diagrams (SO, OAM, MD), pp. 263–277.
ICGT-2012-HeckelEGH #concurrent #graph transformation #parallel: Parallelism and Concurrency of Stochastic Graph Transformations (RH, HE, UG, FH), pp. 96–110.
ICGT-2012-KrauseG #graph transformation: Probabilistic Graph Transformation Systems (CK, HG), pp. 311–325.
CIKM-2012-BerneckerEKRZ #database #fuzzy #ranking: Probabilistic ranking in fuzzy object databases (TB, TE, HPK, MR, AZ), pp. 2647–2650.
CIKM-2012-EmrichKNRSZ #graph #monte carlo #nondeterminism #query: Exploration of monte-carlo based probabilistic query processing in uncertain graphs (TE, HPK, JN, MR, AS, AZ), pp. 2728–2730.
CIKM-2012-HuangCLL #predict #process #social #using: Predicting aggregate social activities using continuous-time stochastic process (SH, MC, BL, DL), pp. 982–991.
CIKM-2012-IntagornL #approach #mining #social: A probabilistic approach to mining geospatial knowledge from social annotations (SI, KL), pp. 1717–1721.
CIKM-2012-KozawaAK #database #gpu #mining #nondeterminism: GPU acceleration of probabilistic frequent itemset mining from uncertain databases (YK, TA, HK), pp. 892–901.
CIKM-2012-KurlandSHRCR #framework #predict: Back to the roots: a probabilistic framework for query-performance prediction (OK, AS, SH, FR, DC, OR), pp. 823–832.
CIKM-2012-Lehrack #database #query: Applying weighted queries on probabilistic databases (SL), pp. 2209–2213.
CIKM-2012-LiKBCL #approach #named #query #recommendation: DQR: a probabilistic approach to diversified query recommendation (RL, BK, BB, RC, EL), pp. 16–25.
CIKM-2012-NiuLGC #problem #ranking: A new probabilistic model for top-k ranking problem (SN, YL, JG, XC), pp. 2519–2522.
CIKM-2012-OrangS #approach #correlation #nondeterminism #query: A probabilistic approach to correlation queries in uncertain time series data (MO, NS), pp. 2229–2233.
CIKM-2012-Sadri #integration #on the: On the foundations of probabilistic information integration (FS), pp. 882–891.
CIKM-2012-SmuckerC #simulation: Stochastic simulation of time-biased gain (MDS, CLAC), pp. 2040–2044.
CIKM-2012-SouihliS #predict #query #xml: Demonstrating ProApproX 2.0: a predictive query engine for probabilistic XML (AS, PS), pp. 2734–2736.
CIKM-2012-WuCLXBZ #matrix: Leveraging tagging for neighborhood-aware probabilistic matrix factorization (LW, EC, QL, LX, TB, LZ), pp. 1854–1858.
CIKM-2012-ZhouLLZ #community #topic: Topic-sensitive probabilistic model for expert finding in question answer communities (GZ, SL, KL, JZ), pp. 1662–1666.
ECIR-2012-Garcia-MoyaAL #modelling #retrieval #sentiment: Combining Probabilistic Language Models for Aspect-Based Sentiment Retrieval (LGM, HAS, RBL), pp. 561–564.
ICML-2012-AhnBW: Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring (SA, AKB, MW), p. 230.
ICML-2012-AvronKKS #performance: Efficient and Practical Stochastic Subgradient Descent for Nuclear Norm Regularization (HA, SK, SPK, VS), p. 46.
ICML-2012-BartokZS #adaptation #algorithm #finite #monitoring: An adaptive algorithm for finite stochastic partial monitoring (GB, NZ, CS), p. 231.
ICML-2012-BonillaR #learning #prototype: Discriminative Probabilistic Prototype Learning (EVB, ARK), p. 155.
ICML-2012-CotterSS #kernel: The Kernelized Stochastic Batch Perceptron (AC, SSS, NS), p. 98.
ICML-2012-DanylukA #feature model: Feature Selection via Probabilistic Outputs (APD, NA), p. 127.
ICML-2012-Honorio #convergence #learning #modelling #optimisation: Convergence Rates of Biased Stochastic Optimization for Learning Sparse Ising Models (JH), p. 144.
ICML-2012-KalyanakrishnanTAS #multi #set: PAC Subset Selection in Stochastic Multi-armed Bandits (SK, AT, PA, PS), p. 34.
ICML-2012-LiuW #modelling #multi: TrueLabel + Confusions: A Spectrum of Probabilistic Models in Analyzing Multiple Ratings (CL, YMW), p. 6.
ICML-2012-MimnoHB: Sparse stochastic inference for latent Dirichlet allocation (DMM, MDH, DMB), p. 197.
ICML-2012-MnihT #algorithm #modelling #performance: A fast and simple algorithm for training neural probabilistic language models (AM, YWT), p. 58.
ICML-2012-OuyangG: Stochastic Smoothing for Nonsmooth Minimizations: Accelerating SGD by Exploiting Structure (HO, AGG), p. 198.
ICML-2012-PaisleyBJ: Variational Bayesian Inference with Stochastic Search (JWP, DMB, MIJ), p. 177.
ICML-2012-RakhlinSS #optimisation: Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization (AR, OS, KS), p. 204.
ICML-2012-RudermanRGP #metric #strict: Tighter Variational Representations of f-Divergences via Restriction to Probability Measures (AR, MDR, DGG, JP), p. 151.
ICML-2012-ShanKRBSR #matrix #predict #using: Gap Filling in the Plant Kingdom — Trait Prediction Using Hierarchical Probabilistic Matrix Factorization (HS, JK, PBR, AB, FS, MR), p. 47.
ICML-2012-YangMJZZ #kernel #learning #multi #programming: Multiple Kernel Learning from Noisy Labels by Stochastic Programming (TY, MM, RJ, LZ, YZ), p. 21.
ICML-2012-YangO #clustering #composition #matrix #rank: Clustering by Low-Rank Doubly Stochastic Matrix Decomposition (ZY, EO), p. 94.
ICPR-2012-Capitaine #equivalence: Set-valued Bayesian inference with probabilistic equivalence (HLC), pp. 2132–2135.
ICPR-2012-CrandallFP #modelling #using #visual notation: Layer-finding in radar echograms using probabilistic graphical models (DJC, GCF, JP), pp. 1530–1533.
ICPR-2012-DuanPJ #multi #realtime: Probabilistic depth map fusion for real-time multi-view stereo (YD, MP, YJ), pp. 368–371.
ICPR-2012-DuanZRTB #automation #automaton #recognition: Timed and probabilistic automata for automatic animal Call Recognition (SD, JZ, PR, MWT, LB), pp. 2910–2913.
ICPR-2012-GhoseMOMLFVCSM #functional #segmentation: A Mumford-Shah functional based variational model with contour, shape, and probability prior information for prostate segmentation (SG, JM, AO, RM, XL, JF, JCV, JC, DS, FM), pp. 121–124.
ICPR-2012-GhoseMOMLFVCSM12a #3d #energy #framework #graph #learning #segmentation: Graph cut energy minimization in a probabilistic learning framework for 3D prostate segmentation in MRI (SG, JM, AO, RM, XL, JF, JCV, JC, DS, FM), pp. 125–128.
ICPR-2012-GkamasCN #problem: A probabilistic formulation of the optical flow problem (TG, GKC, CN), pp. 754–757.
ICPR-2012-HagiyaK #adaptation: Probabilistic keyboard adaptable to user and operating style based on syllable HMMs (TH, TK), pp. 65–68.
ICPR-2012-HanWHBR #generative #graph: Sampling graphs from a probabilistic generative model (LH, RCW, ERH, LB, PR), pp. 1643–1646.
ICPR-2012-LiuLS #documentation #image #modelling #using #visual notation: Document image matching using probabilistic graphical models (LL, YL, CYS), pp. 637–640.
ICPR-2012-MacriniWLG #parsing #recognition: Probabilistic shape parsing for view-based object recognition (DM, CW, RL, MG), pp. 2303–2305.
ICPR-2012-RoyG #detection #framework #image #locality: A probabilistic framework for logo detection and localization in natural scene images (AR, UG), pp. 2051–2054.
ICPR-2012-ScandaliarisS #distance #image #invariant #representation: Probabilistic invariant image representation and associated distance measure (JS, AS), pp. 3569–3572.
ICPR-2012-WangJ12a #approach #novel #recognition: A novel probabilistic approach utilizing clip attribute as hidden knowledge for event recognition (XW, QJ), pp. 3382–3385.
KDD-2012-ChattopadhyayWFDPY: Batch mode active sampling based on marginal probability distribution matching (RC, ZW, WF, ID, SP, JY), pp. 741–749.
KDD-2012-ZhenY #learning #multimodal: A probabilistic model for multimodal hash function learning (YZ, DYY), pp. 940–948.
KDIR-2012-BarbieriBCMR #modelling #recommendation #sequence: Probabilistic Sequence Modeling for Recommender Systems (NB, AB, MC, GM, ER), pp. 75–84.
RecSys-2012-PraweshP #feedback #recommendation: Probabilistic news recommender systems with feedback (SP, BP), pp. 257–260.
SIGIR-2012-JungL #matrix: Inferring missing relevance judgments from crowd workers via probabilistic matrix factorization (HJJ, ML), pp. 1095–1096.
SIGIR-2012-NishidaHF #classification #detection #twitter #word: Improving tweet stream classification by detecting changes in word probability (KN, TH, KF), pp. 971–980.
SIGIR-2012-ZhaoHW #information retrieval: Rewarding term location information to enhance probabilistic information retrieval (JZ, JXH, SW), pp. 1137–1138.
POPL-2012-BartheKOB #difference #privacy #reasoning #relational: Probabilistic relational reasoning for differential privacy (GB, BK, FO, SZB), pp. 97–110.
POPL-2012-BhatAVG #type system: A type theory for probability density functions (SB, AA, RWV, AGG), pp. 545–556.
QAPL-2012-CormieBowinsB #ltl #model checking: Measuring Progress of Probabilistic LTL Model Checking (ECB, FvB), pp. 33–47.
RE-2012-CailliauL #analysis #framework: A probabilistic framework for goal-oriented risk analysis (AC, AvL), pp. 201–210.
ICSE-2012-SongHLSLD #approach #model checking #multi: Analyzing multi-agent systems with probabilistic model checking approach (SS, JH, YL, JS, HfL, JSD), pp. 1337–1340.
SAC-2012-BoumazaB #collaboration: Stochastic search for global neighbors selection in collaborative filtering (AMB, AB), pp. 232–237.
SAC-2012-MenorPB #kernel #predict #using: Probabilistic prediction of protein phosphorylation sites using kernel machines (MM, GP, KB), pp. 1393–1398.
SAC-2012-MinervinidF #concept #learning #logic: Learning probabilistic Description logic concepts: under different Assumptions on missing knowledge (PM, Cd, NF), pp. 378–383.
SAC-2012-SioutasPKT #named #network #query: SART: dynamic P2P query processing in sensor networks with probabilistic guarantees (SS, AP, IK, DT), pp. 847–852.
SAC-2012-ThanhZ #algorithm #simulation: Tree-based search for stochastic simulation algorithm (VHT, RZ), pp. 1415–1416.
CASE-2012-ChenK #polynomial: Polynomial test for Stochastic Diagnosability of discrete event systems (JC, RK), pp. 521–526.
CASE-2012-KimM #modelling #on the #random #throughput: On the throughput of deterministic flow lines with random state dependent setups: Stochastic models and applications (WsK, JRM), pp. 650–655.
DAC-2012-SloanSK #design #on the: On software design for stochastic processors (JS, JS, RK), pp. 918–923.
DATE-2012-AisoposMIIN #named: PCASA: Probabilistic control-adjusted Selective Allocation for shared caches (KA, JM, RI, RI, DN), pp. 473–478.
DATE-2012-AxerSE #bound: Probabilistic response time bound for CAN messages with arbitrary deadlines (PA, MS, RE), pp. 1114–1117.
DATE-2012-LinWCCCHYS #analysis #functional #mutation testing: A probabilistic analysis method for functional qualification under Mutation Analysis (HYL, CYW, SCC, YCC, HMC, CYH, YCY, CCS), pp. 147–152.
DATE-2012-QuintonEBY #analysis #challenge #roadmap: Challenges and new trends in probabilistic timing analysis (SQ, RE, DB, PMY), pp. 810–815.
HPCA-2012-BalakrishnanS #behaviour #named #using: WEST: Cloning data cache behavior using Stochastic Traces (GB, YS), pp. 387–398.
ESOP-2012-CousotM #abstract interpretation: Probabilistic Abstract Interpretation (PC, MM), pp. 169–193.
FoSSaCS-2012-BernardoNL #nondeterminism #process #testing: Revisiting Trace and Testing Equivalences for Nondeterministic and Probabilistic Processes (MB, RDN, ML), pp. 195–209.
FoSSaCS-2012-ChenBW #complexity #on the #similarity: On the Complexity of Computing Probabilistic Bisimilarity (DC, FvB, JW), pp. 437–451.
FoSSaCS-2012-DArgenioL #abstraction #bisimulation #congruence #specification: Probabilistic Transition System Specification: Congruence and Full Abstraction of Bisimulation (PRD, MDL), pp. 452–466.
FoSSaCS-2012-KieferMOWW #automaton #complexity #equivalence #on the #problem: On the Complexity of the Equivalence Problem for Probabilistic Automata (SK, ASM, JO, BW, JW), pp. 467–481.
FoSSaCS-2012-NainV: Synthesizing Probabilistic Composers (SN, MYV), pp. 421–436.
STOC-2012-EtessamiSY #algorithm #branch #context-free grammar #multi #polynomial #process: Polynomial time algorithms for multi-type branching processes and stochastic context-free grammars (KE, AS, MY), pp. 579–588.
STOC-2012-KuperbergLP #combinator: Probabilistic existence of rigid combinatorial structures (GK, SL, RP), pp. 1091–1106.
TACAS-2012-ChenFKPS #automation #verification: Automatic Verification of Competitive Stochastic Systems (TC, VF, MZK, DP, AS), pp. 315–330.
CAV-2012-EsparzaGK #proving #source code #termination #using: Proving Termination of Probabilistic Programs Using Patterns (JE, AG, SK), pp. 123–138.
CAV-2012-KieferMOWW #named #source code: APEX: An Analyzer for Open Probabilistic Programs (SK, ASM, JO, BW, JW), pp. 693–698.
CAV-2012-KomuravelliPC #abstraction #refinement: Assume-Guarantee Abstraction Refinement for Probabilistic Systems (AK, CSP, EMC), pp. 310–326.
CAV-2012-SongSLD #model checking #realtime: A Model Checker for Hierarchical Probabilistic Real-Time Systems (SS, JS, YL, JSD), pp. 705–711.
ICLP-2012-SatoM #infinity: Tabling for infinite probability computation (TS, PM), pp. 348–358.
ICLP-J-2012-GorlinRS #logic programming #model checking: Model checking with probabilistic tabled logic programming (AG, CRR, SAS), pp. 681–700.
ICLP-J-2012-IslamRR #logic programming #random #source code: Inference in probabilistic logic programs with continuous random variables (MAI, CRR, IVR), pp. 505–523.
ISSTA-2012-GeldenhuysDV #execution #symbolic computation: Probabilistic symbolic execution (JG, MBD, WV), pp. 166–176.
LICS-2012-ChatterjeeD #game studies #how: Partial-Observation Stochastic Games: How to Win When Belief Fails (KC, LD), pp. 175–184.
LICS-2012-ChatterjeeT #automaton #decidability #infinity #problem #word: Decidable Problems for Probabilistic Automata on Infinite Words (KC, MT), pp. 185–194.
LICS-2012-FijalkowGO #automaton #problem: Deciding the Value 1 Problem for Probabilistic Leaktight Automata (NF, HG, YO), pp. 295–304.
LICS-2012-KomuravelliPC #learning: Learning Probabilistic Systems from Tree Samples (AK, CSP, EMC), pp. 441–450.
LICS-2012-McIverMM #information management #nondeterminism: A Kantorovich-Monadic Powerdomain for Information Hiding, with Probability and Nondeterminism (AM, LM, CM), pp. 461–470.
SAT-2012-BalintS: Choosing Probability Distributions for Stochastic Local Search and the Role of Make versus Break (AB, US), pp. 16–29.
VMCAI-2012-Bugaychenko #diagrams #model checking #multi #on the: On Application of Multi-Rooted Binary Decision Diagrams to Probabilistic Model Checking (DB), pp. 104–118.
VMCAI-2012-SackZ #framework: A General Framework for Probabilistic Characterizing Formulae (JS, LZ), pp. 396–411.
DocEng-2011-Damera-VenkataBO #automation #composition #documentation: Probabilistic document model for automated document composition (NDV, JB, EOS), pp. 3–12.
ICDAR-2011-AlvaroSB #2d #context-free grammar #recognition #using: Recognition of Printed Mathematical Expressions Using Two-Dimensional Stochastic Context-Free Grammars (FA, JAS, JMB), pp. 1225–1229.
ICDAR-2011-CelikY #2d #graph grammar #recognition #using: Probabilistic Mathematical Formula Recognition Using a 2D Context-Free Graph Grammar (MC, BAY), pp. 161–166.
ICDAR-2011-SituLT #image #locality #using #web: Text Localization in Web Images Using Probabilistic Candidate Selection Model (LS, RL, CLT), pp. 1359–1363.
SIGMOD-2011-IoannouNNV #database #named: LinkDB: a probabilistic linkage database system (EI, WN, CN, YV), pp. 1307–1310.
SIGMOD-2011-KanagalLD #analysis #database #evaluation #query #robust: Sensitivity analysis and explanations for robust query evaluation in probabilistic databases (BK, JL, AD), pp. 841–852.
SIGMOD-2011-LianC #graph #performance #query #rdf: Efficient query answering in probabilistic RDF graphs (XL, LC), pp. 157–168.
SIGMOD-2011-LuADT #named #query: Schema-as-you-go: on probabilistic tagging and querying of wide tables (ML, DA, BTD, AKHT), pp. 181–192.
SIGMOD-2011-SenellartS #approximate #lightweight #named #query: ProApproX: a lightweight approximation query processor over probabilistic trees (PS, AS), pp. 1295–1298.
SIGMOD-2011-ZhaiLG #algorithm #named #similarity: ATLAS: a probabilistic algorithm for high dimensional similarity search (JZ, YL, JG), pp. 997–1008.
VLDB-2011-BerneckerEKRZZ #nearest neighbour #nondeterminism #performance #query: Efficient Probabilistic Reverse Nearest Neighbor Query Processing on Uncertain Data (TB, TE, HPK, MR, SZ, AZ), pp. 669–680.
VLDB-2011-KhannaRT #database #difference #query: Queries with Difference on Probabilistic Databases (SK, SR, VT), pp. 1051–1062.
VLDB-2011-PengDL #nondeterminism #optimisation #query: Optimizing Probabilistic Query Processing on Continuous Uncertain Data (LP, YD, AL), pp. 1169–1180.
VLDB-2012-KumarR11 #using: Probabilistic Management of OCR Data using an RDBMS (AK, CR), pp. 322–333.
VLDB-2012-SuchanekAS11 #named: PARIS: Probabilistic Alignment of Relations, Instances, and Schema (FMS, SA, PS), pp. 157–168.
ICSM-2011-BakotaHKFG #quality: A probabilistic software quality model (TB, PH, PK, RF, TG), pp. 243–252.
ICALP-v1-2011-BorosEFGMM #analysis #approximate #game studies: Stochastic Mean Payoff Games: Smoothed Analysis and Approximation Schemes (EB, KME, MF, VG, KM, BM), pp. 147–158.
ICALP-v1-2011-HuangP #game studies: Automatizability and Simple Stochastic Games (LH, TP), pp. 605–617.
ICALP-v2-2011-BrazdilBEK #approximate #game studies #termination: Approximating the Termination Value of One-Counter MDPs and Stochastic Games (TB, VB, KE, AK), pp. 332–343.
ICALP-v2-2011-BrazdilKKV #analysis #bound #recursion #runtime #source code: Runtime Analysis of Probabilistic Programs with Unbounded Recursion (TB, SK, AK, IHV), pp. 319–331.
ICALP-v2-2011-CrafaR #abstract interpretation #algorithm #bisimulation #simulation: Probabilistic Bisimulation and Simulation Algorithms by Abstract Interpretation (SC, FR), pp. 295–306.
ICALP-v2-2011-ZhangB #model checking: A Progress Measure for Explicit-State Probabilistic Model-Checkers (XZ, FvB), pp. 283–294.
SFM-2011-ForejtKNP #automation #verification: Automated Verification Techniques for Probabilistic Systems (VF, MZK, GN, DP), pp. 53–113.
AIIDE-2011-DereszynskiHFDHU #behaviour #game studies #learning #modelling #realtime: Learning Probabilistic Behavior Models in Real-Time Strategy Games (EWD, JH, AF, TGD, TTH, MU).
AIIDE-2011-Gold #modelling: Trigram Timmies and Bayesian Johnnies: Probabilistic Models of Personality in Dominion (KG).
CIKM-2011-GaoL #adaptation #analysis #classification #sentiment #using: A cross-domain adaptation method for sentiment classification using probabilistic latent analysis (SG, HL), pp. 1047–1052.
CIKM-2011-HofmannWR: A probabilistic method for inferring preferences from clicks (KH, SW, MdR), pp. 249–258.
CIKM-2011-LianLC #consistency #database #low cost: Cost-efficient repair in inconsistent probabilistic databases (XL, YL, LC), pp. 1731–1736.
CIKM-2011-QuC: Sparse structured probabilistic projections for factorized latent spaces (XQ, XC), pp. 1389–1394.
CIKM-2011-SachanCFS #community #network #social #topic: Probabilistic model for discovering topic based communities in social networks (MS, DC, TAF, LVS), pp. 2349–2352.
CIKM-2011-SoodL #detection #using: Probabilistic near-duplicate detection using simhash (SS, DL), pp. 1117–1126.
CIKM-2011-TomasevRMI #approach #classification #nearest neighbour: A probabilistic approach to nearest-neighbor classification: naive hubness bayesian kNN (NT, MR, DM, MI), pp. 2173–2176.
CIKM-2011-WangC #information retrieval #modelling #ranking #statistics: Statistical information retrieval modelling: from the probability ranking principle to recent advances in diversity, portfolio theory, and beyond (JW, KCT), pp. 2603–2604.
ICML-2011-AgovicBC #matrix: Probabilistic Matrix Addition (AA, AB, SC), pp. 1025–1032.
ICML-2011-FrancZS #modelling: Support Vector Machines as Probabilistic Models (VF, AZ, BS), pp. 665–672.
ICML-2011-GuanDJ #feature model: A Unified Probabilistic Model for Global and Local Unsupervised Feature Selection (YG, JGD, MIJ), pp. 1073–1080.
ICML-2011-LeeW #identification #learning #online: Manifold Identification of Dual Averaging Methods for Regularized Stochastic Online Learning (SL, SJW), pp. 1121–1128.
ICML-2011-MachartPARG #kernel #learning #rank: Stochastic Low-Rank Kernel Learning for Regression (PM, TP, SA, LR, HG), pp. 969–976.
ICML-2011-Sohl-DicksteinBD #learning: Minimum Probability Flow Learning (JSD, PB, MRD), pp. 905–912.
ICML-2011-WellingT #learning: Bayesian Learning via Stochastic Gradient Langevin Dynamics (MW, YWT), pp. 681–688.
KDD-2011-DengHZYL #modelling #network #topic: Probabilistic topic models with biased propagation on heterogeneous information networks (HD, JH, BZ, YY, CXL), pp. 1271–1279.
KDD-2011-GemullaNHS #distributed #matrix #scalability: Large-scale matrix factorization with distributed stochastic gradient descent (RG, EN, PJH, YS), pp. 69–77.
KDIR-2011-Aladjem #modelling: Probabilistic Modeling, Projection Pursuit and Blind Source Separation (MA), p. 9.
KDIR-2011-BarbieriCMR #approach #clustering: Characterizing Relationships through Co-clustering — A Probabilistic Approach (NB, GC, GM, ER), pp. 64–73.
KEOD-2011-IshakLA #approach #learning #modelling #ontology #visual notation: A Two-way Approach for Probabilistic Graphical Models Structure Learning and Ontology Enrichment (MBI, PL, NBA), pp. 189–194.
RecSys-2011-JamaliHE #network #rating #recommendation #social: A generalized stochastic block model for recommendation in social rating networks (MJ, TH, ME), pp. 53–60.
RecSys-2011-JojicSB #similarity: A probabilistic definition of item similarity (OJ, MS, NB), pp. 229–236.
RecSys-2011-PizzatoS #collaboration #people #recommendation: Stochastic matching and collaborative filtering to recommend people to people (LASP, CS), pp. 341–344.
RecSys-2011-XinS #matrix #multi #recommendation: Multi-value probabilistic matrix factorization for IP-TV recommendations (YX, HS), pp. 221–228.
SEKE-2011-El-KharboutlyG #analysis #architecture #concurrent #reliability #using: Architecture-based Reliability Analysis of Concurrent Software Applications using Stochastic Reward Nets (REK, SSG), pp. 635–639.
SIGIR-2011-CetintasCSSD #modelling #online: Forecasting counts of user visits for online display advertising with probabilistic latent class models (SC, DC, LS, BS, ZD), pp. 1217–1218.
SIGIR-2011-CetintasRSF #identification #modelling #network #people #social: Identifying similar people in professional social networks with discriminative probabilistic models (SC, MR, LS, YF), pp. 1209–1210.
SIGIR-2011-MaLKL #modelling #recommendation #web: Probabilistic factor models for web site recommendation (HM, CL, IK, MRL), pp. 265–274.
SIGIR-2011-ZhaoHH #information retrieval #named #using: CRTER: using cross terms to enhance probabilistic information retrieval (JZ, JXH, BH), pp. 155–164.
SIGIR-2011-ZhouHH #ad hoc #estimation #using: Enhancing ad-hoc relevance weighting using probability density estimation (XZ, JXH, BH), pp. 175–184.
LOPSTR-2011-SneyersS #source code #termination: Probabilistic Termination of CHRiSM Programs (JS, DDS), pp. 221–236.
PEPM-2011-Rinard #bound #program analysis #program transformation #source code: Probabilistic accuracy bounds for perforated programs: a new foundation for program analysis and transformation (MCR), pp. 79–80.
PLDI-2011-BeckmanN #composition #scalability #specification #type system: Probabilistic, modular and scalable inference of typestate specifications (NEB, AVN), pp. 211–221.
QAPL-2011-AssouramouD #analysis #hybrid: Analysis of Non-Linear Probabilistic Hybrid Systems (JA, JD), pp. 104–119.
QAPL-2011-BortolussiGH: HYPE with stochastic events (LB, VG, JH), pp. 120–133.
QAPL-2011-DengGHM #process #testing: Real-Reward Testing for Probabilistic Processes (YD, RJvG, MH, CM), pp. 61–73.
QAPL-2011-SongNN #π-calculus: A Stochastic Broadcast π-Calculus (LS, FN, BFN), pp. 74–88.
QAPL-2011-TracolDZ #automaton: Computing Distances between Probabilistic Automata (MT, JD, AZ), pp. 148–162.
SAS-2011-EsparzaG #abstraction: Probabilistic Abstractions with Arbitrary Domains (JE, AG), pp. 334–350.
ASE-2011-WongC #dependence: Generalizing evolutionary coupling with stochastic dependencies (SW, YC), pp. 293–302.
ESEC-FSE-2011-RamamurthiRS #analysis #data flow #graph #using: Probabilistic dataflow analysis using path profiles on structure graphs (AR, SR, YNS), pp. 512–515.
ICSE-2011-FilieriGT #model checking #performance #runtime: Run-time efficient probabilistic model checking (AF, CG, GT), pp. 341–350.
SAC-2011-MitraZA #approach #experience #metric #pervasive #quality: A probabilistic context-aware approach for quality of experience measurement in pervasive systems (KM, ABZ, CÅ), pp. 419–424.
SAC-2011-TeixeiraLOM #modelling: Planning service agreements in soa-based systems through stochastic models (MT, RMFL, CALO, PRMM), pp. 1576–1581.
CASE-2011-ChuYSS #simulation #validation: Validation of stochastic traffic flow model with microscopic traffic simulation (KCC, LY, RS, KS), pp. 672–677.
CASE-2011-MovafaghpourM #approach #linear #programming: A linear programming approach for probabilistic robot path planning with missing information of outcomes (MAM, EM), pp. 126–132.
CC-2011-SunZC #analysis #java #points-to: Probabilistic Points-to Analysis for Java (QS, JZ, YC), pp. 62–81.
DAC-2011-AadithyaVDR #impact analysis #named #predict #random: MUSTARD: a coupled, stochastic/deterministic, discrete/continuous technique for predicting the impact of random telegraph noise on SRAMs and DRAMs (KVA, SV, AD, JSR), pp. 292–297.
DAC-2011-GongYH #analysis #monte carlo #orthogonal #performance: Fast non-monte-carlo transient noise analysis for high-precision analog/RF circuits by stochastic orthogonal polynomials (FG, HY, LH), pp. 298–303.
DAC-2011-IqbalSH #dependence #fault #monte carlo #named #power management #scheduling: SEAL: soft error aware low power scheduling by Monte Carlo state space under the influence of stochastic spatial and temporal dependencies (NI, MAS, JH), pp. 134–139.
DATE-2011-AvinashENPP #design #energy: Energy parsimonious circuit design through probabilistic pruning (LA, CCE, JLN, KVP, CP), pp. 764–769.
DATE-2011-MaricauG #analysis #reliability: Stochastic circuit reliability analysis (EM, GGEG), pp. 1285–1290.
FASE-2011-FengKP #automation #composition #learning #reasoning: Automated Learning of Probabilistic Assumptions for Compositional Reasoning (LF, MZK, DP), pp. 2–17.
FoSSaCS-2011-Mio #calculus #independence #μ-calculus: Probabilistic Modal μ-Calculus with Independent Product (MM), pp. 290–304.
STOC-2011-HansenKLMT #algorithm #game studies: Exact algorithms for solving stochastic games: extended abstract (KAH, MK, NL, PBM, EPT), pp. 205–214.
TACAS-2011-BartocciGKRS: Model Repair for Probabilistic Systems (EB, RG, PK, CRR, SAS), pp. 326–340.
TACAS-2011-ForejtKNPQ #multi #verification: Quantitative Multi-objective Verification for Probabilistic Systems (VF, MZK, GN, DP, HQ), pp. 112–127.
TACAS-2011-KieferW #on the #parallel #process #source code: On Probabilistic Parallel Programs with Process Creation and Synchronisation (SK, DW), pp. 296–310.
TACAS-2011-TeigeF #problem #satisfiability: Generalized Craig Interpolation for Stochastic Boolean Satisfiability Problems (TT, MF), pp. 158–172.
TACAS-2011-TimmerSP #confluence #reduction: Confluence Reduction for Probabilistic Systems (MT, MS, JvdP), pp. 311–325.
CADE-2011-KlinovP #hybrid #satisfiability: A Hybrid Method for Probabilistic Satisfiability (PK, BP), pp. 354–368.
CADE-2011-Platzer #difference #hybrid #logic #source code: Stochastic Differential Dynamic Logic for Stochastic Hybrid Programs (AP), pp. 446–460.
CAV-2011-BrazdilKK #analysis #bound #performance #source code: Efficient Analysis of Probabilistic Programs with an Unbounded Counter (TB, SK, AK), pp. 208–224.
CAV-2011-KieferMOWW #automaton #equivalence: Language Equivalence for Probabilistic Automata (SK, ASM, JO, BW, JW), pp. 526–540.
CAV-2011-KwiatkowskaNP #realtime #verification: PRISM 4.0: Verification of Probabilistic Real-Time Systems (MZK, GN, DP), pp. 585–591.
CAV-2011-SistlaZF: Monitorability of Stochastic Dynamical Systems (APS, MZ, YF), pp. 720–736.
CSL-2011-LustigNV #component #synthesis: Synthesis from Probabilistic Components (YL, SN, MYV), pp. 412–427.
ICLP-2011-MolinaroSS #abduction #logic: Abduction in Annotated Probabilistic Temporal Logic (CM, AS, VSS), pp. 240–250.
ICLP-2011-NicholsonSS #generative #logic #music #using: Improving the Outcome of a Probabilistic Logic Music System Generator by Using Perlin Noise (CJN, DDS, JS), pp. 231–239.
ICLP-J-2011-GutmannTKBR #logic #programming: The magic of logical inference in probabilistic programming (BG, IT, AK, MB, LDR), pp. 663–680.
ICTSS-2011-Nunez #testing: Formal Testing of Timed and Probabilistic Systems (MN), pp. 9–14.
LICS-2011-EhrhardPT: The Computational Meaning of Probabilistic Coherence Spaces (TE, MP, CT), pp. 87–96.
VMCAI-2011-ChadhaSV #automaton: Probabilistic Büchi Automata with Non-extremal Acceptance Thresholds (RC, APS, MV), pp. 103–117.
VMCAI-2011-DelahayeKLLPSW #automaton: Abstract Probabilistic Automata (BD, JPK, KGL, AL, MLP, FS, AW), pp. 324–339.
PODS-2010-DalviSS #algebra #query: Computing query probability with incidence algebras (NND, KS, DS), pp. 203–214.
PODS-2010-DeutchKM #fixpoint #markov #on the #query: On probabilistic fixpoint and Markov chain query languages (DD, CK, TM), pp. 215–226.
SIGMOD-2010-ChenMK #database #query: GRN model of probabilistic databases: construction, transition and querying (RC, YM, IK), pp. 291–302.
SIGMOD-2010-JestesLYY #similarity #string: Probabilistic string similarity joins (JJ, FL, ZY, KY), pp. 327–338.
SIGMOD-2010-KanagalD #correlation #database: Lineage processing over correlated probabilistic databases (BK, AD), pp. 675–686.
SIGMOD-2010-LianCS #consistency #database #query: Consistent query answers in inconsistent probabilistic databases (XL, LC, SS), pp. 303–314.
SIGMOD-2010-PerezAJ #evaluation #query: Evaluation of probabilistic threshold queries in MCDB (LLP, SA, CMJ), pp. 687–698.
VLDB-2010-BenediktKOS #markov #xml: Probabilistic XML via Markov Chains (MB, EK, DO, PS), pp. 770–781.
VLDB-2010-LianC #set #similarity: Set Similarity Join on Probabilistic Data (XL, LC), pp. 650–659.
VLDB-2010-LiD #dataset #ranking: Ranking Continuous Probabilistic Datasets (JL, AD), pp. 638–649.
VLDB-2010-SenDG #database #evaluation #query: Read-Once Functions and Query Evaluation in Probabilistic Databases (PS, AD, LG), pp. 1068–1079.
VLDB-2010-WangFGH #information management #query: Querying Probabilistic Information Extraction (DZW, MJF, MNG, JMH), pp. 1057–1067.
VLDB-2010-WickMM #database #graph #scalability: Scalable Probabilistic Databases with Factor Graphs and MCMC (MLW, AM, GM), pp. 794–804.
VLDB-2010-XuZTY #data-driven #database #distance #effectiveness #performance #similarity: Efficient and Effective Similarity Search over Probabilistic Data based on Earth Mover’s Distance (JX, ZZ, AKHT, GY), pp. 758–769.
VLDB-2011-TodaCSM10 #approach #automation #interface #web: A Probabilistic Approach for Automatically Filling Form-Based Web Interfaces (GAT, EC, ASdS, ESdM), pp. 151–160.
EDM-2010-KhodeirWDH #abduction #difference #network #student #using: Inferring the Differential Student Model in a Probabilistic Domain Using Abduction inference in Bayesian networks (NK, NMW, NMD, NH), pp. 299–300.
CSMR-2010-CorazzaMS #approach #clustering #towards: A Probabilistic Based Approach towards Software System Clustering (AC, SDM, GS), pp. 88–96.
PASTE-2010-FengG #fault #learning #locality #modelling: Learning universal probabilistic models for fault localization (MF, RG), pp. 81–88.
ICALP-v2-2010-GimbertO #automaton #decidability #finite #problem #word: Probabilistic Automata on Finite Words: Decidable and Undecidable Problems (HG, YO), pp. 527–538.
ICALP-v2-2010-McIverMM #composition: Compositional Closure for Bayes Risk in Probabilistic Noninterference (AM, LM, CM), pp. 223–235.
LATA-2010-MarschallR #algorithm #analysis #automaton #pattern matching: Exact Analysis of Horspool’s and Sunday’s Pattern Matching Algorithms with Probabilistic Arithmetic Automata (TM, SR), pp. 439–450.
LATA-2010-WeinbergN #context-free grammar: Extending Stochastic Context-Free Grammars for an Application in Bioinformatics (FW, MEN), pp. 585–595.
IFM-2010-FranzleTE #hybrid #smt: Satisfaction Meets Expectations — Computing Expected Values of Probabilistic Hybrid Systems with SMT (MF, TT, AE), pp. 168–182.
IFM-2010-TarasyukTL #modelling #towards: Towards Probabilistic Modelling in Event-B (AT, ET, LL), pp. 275–289.
SFM-2010-PierroHW #program analysis #semantics: Probabilistic Semantics and Program Analysis (ADP, CH, HW), pp. 1–42.
IFL-2010-TorontoM: From Bayesian Notation to Pure Racket via Discrete Measure-Theoretic Probability in λ ZFC (NT, JM), pp. 89–104.
CIG-2010-ChapelBM #detection #game studies #online: Probabilistic approaches to cheating detection in online games (LC, DB, DM), pp. 195–201.
GT-VMT-2010-TorriniHRB #graph transformation: Stochastic Graph Transformation with Regions (PT, RH, IR, GB).
ICGT-2010-Donyina #modelling #resource management #simulation: Stochastic Modelling and Simulation of Dynamic Resource Allocation (AD), pp. 388–390.
CAiSE-2010-BlancoCMP #data flow #modelling: Probabilistic Models to Reconcile Complex Data from Inaccurate Data Sources (LB, VC, PM, PP), pp. 83–97.
EDOC-2010-NarmanBKJ #analysis #hybrid #modelling #quality #relational: Hybrid Probabilistic Relational Models for System Quality Analysis (PN, MB, JK, PJ), pp. 57–66.
CIKM-2010-ChenHZLRHP #automation #image #topic: A probabilistic topic-connection model for automatic image annotation (XC, XH, ZZ, CL, GR, TH, EKP), pp. 899–908.
CIKM-2010-LinYC #query: Selective data acquisition for probabilistic K-NN query (YCL, DNY, MSC), pp. 1357–1360.
CIKM-2010-RaghavanI #retrieval #theory and practice: Probabilistic first pass retrieval for search advertising: from theory to practice (HR, RI), pp. 1019–1028.
CIKM-2010-WangCLC #approach #mining #modelling: Accelerating probabilistic frequent itemset mining: a model-based approach (LW, RC, SDL, DWLC), pp. 429–438.
CIKM-2010-ZhangSZBA #documentation #mining #named #parallel #topic: PTM: probabilistic topic mapping model for mining parallel document collections (DZ, JS, CZ, AB, NA), pp. 1653–1656.
ECIR-2010-PapapetrouSF #clustering #network #peer-to-peer: Text Clustering for Peer-to-Peer Networks with Probabilistic Guarantees (OP, WS, NF), pp. 293–305.
ECIR-2010-ZucconA #documentation #quantum #rank #ranking #using: Using the Quantum Probability Ranking Principle to Rank Interdependent Documents (GZ, LA), pp. 357–369.
ICML-2010-DembczynskiCH #classification #multi: Bayes Optimal Multilabel Classification via Probabilistic Classifier Chains (KD, WC, EH), pp. 279–286.
ICML-2010-LangT #reasoning #relational: Probabilistic Backward and Forward Reasoning in Stochastic Relational Worlds (TL, MT), pp. 583–590.
ICML-2010-Masnadi-ShiraziV #elicitation: Risk minimization, probability elicitation, and cost-sensitive SVMs (HMS, NV), pp. 759–766.
ICPR-2010-AkceB: A Probabilistic Language Model for Hand Drawings (AA, TB), pp. 109–112.
ICPR-2010-AkgulE #approach #automation: A Probabilistic Information Fusion Approach to MR-based Automated Diagnosis of Dementia (CBA, AE), pp. 265–268.
ICPR-2010-AmateR #learning #modelling: Learning Probabilistic Models of Contours (LA, MJR), pp. 645–648.
ICPR-2010-AvenelMP #set: Stochastic Filtering of Level Sets for Curve Tracking (CA, ÉM, PP), pp. 3553–3556.
ICPR-2010-BruneauGP #parametricity: Aggregation of Probabilistic PCA Mixtures with a Variational-Bayes Technique Over Parameters (PB, MG, FP), pp. 702–705.
ICPR-2010-BuloP #clustering #difference #using: Probabilistic Clustering Using the Baum-Eagon Inequality (SRB, MP), pp. 1429–1432.
ICPR-2010-HuangCWC #modelling: Probabilistic Modeling of Dynamic Traffic Flow across Non-overlapping Camera Views (CH, WcC, SJW, JHC), pp. 3332–3335.
ICPR-2010-KimLL #approach #segmentation: A Unified Probabilistic Approach to Feature Matching and Object Segmentation (THK, KML, SUL), pp. 464–467.
ICPR-2010-PrasadBSCN #adaptation #recognition: Stochastic Segment Model Adaptation for Offline Handwriting Recognition (RP, AB, KS, HC, PN), pp. 1993–1996.
ICPR-2010-PuS #learning #verification: Probabilistic Measure for Signature Verification Based on Bayesian Learning (DP, SNS), pp. 1188–1191.
ICPR-2010-SethiC #analysis #motivation #process #video: A Neurobiologically Motivated Stochastic Method for Analysis of Human Activities in Video (RJS, AKRC), pp. 281–285.
ICPR-2010-WijnhovenW #detection #performance #using: Fast Training of Object Detection Using Stochastic Gradient Descent (RGJW, PHNdW), pp. 424–427.
KDD-2010-SunCCC #mining #nondeterminism: Mining uncertain data with probabilistic guarantees (LS, RC, DWC, JC), pp. 273–282.
KDD-2010-YangO #feature model #predict #using: Feature selection for support vector regression using probabilistic prediction (JBY, CJO), pp. 343–352.
KDD-2010-YinXHD #personalisation #predict: A probabilistic model for personalized tag prediction (DY, ZX, LH, BDD), pp. 959–968.
KDD-2010-ZouGL #database #graph #nondeterminism #semantics: Discovering frequent subgraphs over uncertain graph databases under probabilistic semantics (ZZ, HG, JL), pp. 633–642.
KR-2010-HajishirziA #reasoning: Reasoning about Deterministic Actions with Probabilistic Prior and Application to Stochastic Filtering (HH, EA).
KR-2010-Kern-IsbernerT #novel #relational #semantics: Novel Semantical Approaches to Relational Probabilistic Conditionals (GKI, MT).
KR-2010-LutzS #logic #nondeterminism: Probabilistic Description Logics for Subjective Uncertainty (CL, LS).
SEKE-2010-WangXLS #debugging #optimisation: A Stochastic Model for Optimizing the Patching Time of Software Bugs (YW, DX, WML, DBS), pp. 88–92.
SIGIR-2010-GuoS: Probabilistic latent maximal marginal relevance (SG, SS), pp. 833–834.
SIGIR-2010-HongSBWJ #classification: A joint probabilistic classification model for resource selection (DH, LS, PB, MW, TJ), pp. 98–105.
SIGIR-2010-Lavrenko #information retrieval #modelling: Introduction to probabilistic models in IR (VL), p. 905.
QAPL-2010-Aldini #approximate #behaviour #equivalence #testing: Approximate Testing Equivalence Based on Time, Probability, and Observed Behavior (AA), pp. 1–15.
QAPL-2010-BarsottiW #abstraction #automation #random #verification: Automatic Probabilistic Program Verification through Random Variable Abstraction (DB, NW), pp. 34–47.
QAPL-2010-CoppoDDGT #calculus: Stochastic Calculus of Wrapped Compartments (MC, FD, MD, EG, AT), pp. 82–98.
QAPL-2010-GeorgievskaA #process #testing: Testing Reactive Probabilistic Processes (SG, SA), pp. 99–113.
QAPL-2010-GuedemannO #analysis #modelling #safety: Probabilistic Model-Based Safety Analysis (MG, FO), pp. 114–128.
QAPL-2010-NdukwuMc #abstraction #approach #independence #source code: An expectation transformer approach to predicate abstraction and data independence for probabilistic programs (UN, AM), pp. 129–143.
SAS-2010-KatoenMMM #automation #generative #invariant #source code: Linear-Invariant Generation for Probabilistic Programs: — Automated Support for Proof-Based Methods (JPK, AM, LM, CCM), pp. 390–406.
ICSE-2010-Meedeniya #architecture #evaluation #incremental #modelling: An incremental methodology for quantitative software architecture evaluation with probabilistic models (IM), pp. 339–340.
SAC-2010-AlmeidaYA #anti #reduction: Probabilistic anti-spam filtering with dimensionality reduction (TAA, AY, JA), pp. 1802–1806.
SAC-2010-AminBFJ #approach: A stochastic approach to candidate disease gene subnetwork extraction (MSA, AB, RLFJ, HMJ), pp. 1534–1538.
SAC-2010-BenaouichaTB #flexibility #query: Flexible document-query matching based on a probabilistic content and structure score combination (MB, MT, MB), pp. 1728–1734.
SAC-2010-CarvalhoCB #constraints #problem #reliability: Probabilistic constraints for reliability problems (EC, JC, PB), pp. 2055–2060.
SAC-2010-DongD #analysis: Analysis of collision probability in unsaturated situation (QD, WD), pp. 772–777.
SAC-2010-GhoulbeigiS #evolution: Probabilistic developmental program evolution (EG, MVdS), pp. 1138–1142.
SAC-2010-KimKMY #multi #network #predict #using: Probabilistic context prediction using time-inferred multiple pattern networks (YHK, WK, KM, YY), pp. 1015–1019.
SAC-2010-Mohy-ud-DinM #detection: Detecting narrow passages in configuration spaces via spectra of probabilistic roadmaps (HMuD, AM), pp. 1294–1298.
SAC-2010-MylavarapuSB #approach #capacity #framework: An optimized capacity planning approach for virtual infrastructure exhibiting stochastic workload (SM, VS, PB), pp. 386–390.
SAC-2010-NinagawaE #modelling #network #predict #using: Link prediction using probabilistic group models of network structure (AN, KE), pp. 1115–1116.
ASPLOS-2010-BurckhardtKMN #debugging #random: A randomized scheduler with probabilistic guarantees of finding bugs (SB, PK, MM, SN), pp. 167–178.
ASPLOS-2010-EyermanE #modelling #scheduling #smt: Probabilistic job symbiosis modeling for SMT processor scheduling (SE, LE), pp. 91–102.
ASPLOS-2010-FengGAM #fault #named #reliability #string: Shoestring: probabilistic soft error reliability on the cheap (SF, SG, AA, SAM), pp. 385–396.
CASE-2010-MacwanNB #approach #bound #multi #novel #online #predict: On-line target-motion prediction for autonomous multirobot search in realistic terrains with time-expanding boundaries: A novel probabilistic approach (AM, GN, BB), pp. 662–667.
CASE-2010-PintoKK #analysis #modelling: A model-based end-to-end toolchain for the probabilistic analysis of complex systems (AP, SK, SK), pp. 994–1000.
CASE-2010-QiC #constraints #optimisation: Stochastic optimization of hydro-thermal system with annual water consumption constraints (YQ, XC), pp. 1001–1006.
DAC-2010-El-MoselhyD: Stochastic dominant singular vectors method for variation-aware extraction (TAEM, LD), pp. 667–672.
DAC-2010-ShanbhagAKJ: Stochastic computation (NRS, RAA, RK, DLJ), pp. 859–864.
DAC-2010-ZitterellS #approach #energy #online #realtime #scheduling: A probabilistic and energy-efficient scheduling approach for online application in real-time systems (TZ, CS), pp. 42–47.
DATE-2010-LauLCB: A general mathematical model of probabilistic ripple-carry adders (MSKL, KVL, YCC, AB), pp. 1100–1105.
DATE-2010-LeemCBJM #architecture #fault #named: ERSA: Error Resilient System Architecture for probabilistic applications (LL, HC, JB, QAJ, SM), pp. 1560–1565.
DATE-2010-NarayananSKJ #scalability: Scalable stochastic processors (SN, JS, RK, DLJ), pp. 335–338.
FASE-2010-TorriniHR #graph transformation #simulation: Stochastic Simulation of Graph Transformation Systems (PT, RH, IR), pp. 154–157.
FoSSaCS-2010-GeorgievskaA #testing: Retaining the Probabilities in Probabilistic Testing Theory (SG, SA), pp. 79–93.
TACAS-2010-HahnHWZ #abstraction #infinity #modelling #named #refinement: PASS: Abstraction Refinement for Infinite Probabilistic Models (EMH, HH, BW, LZ), pp. 353–357.
TACAS-2010-KwiatkowskaNPQ #verification: Assume-Guarantee Verification for Probabilistic Systems (MZK, GN, DP, HQ), pp. 23–37.
CAV-2010-ChatterjeeHJR #game studies #named: Gist: A Solver for Probabilistic Games (KC, TAH, BJ, AR), pp. 665–669.
CAV-2010-ChatterjeeHJS: Measuring and Synthesizing Systems in Probabilistic Environments (KC, TAH, BJ, RS), pp. 380–395.
CAV-2010-ZhangSRHH #hybrid #safety #verification: Safety Verification for Probabilistic Hybrid Systems (LZ, ZS, SR, HH, EMH), pp. 196–211.
ICLP-2010-Fierens10 #logic #modelling #performance: Improving the Efficiency of Gibbs Sampling for Probabilistic Logical Models by Means of Program Specialization (DF), pp. 74–83.
ICLP-2010-MantadelisJ10: Dedicated Tabling for a Probabilistic Setting (TM, GJ), pp. 124–133.
ICLP-2010-SimariS10 #abduction #logic programming #source code: Abductive Inference in Probabilistic Logic Programs (GIS, VSS), pp. 192–201.
ICLP-J-2010-SneyersMVKS #learning #logic: CHR(PRISM)-based probabilistic logic learning (JS, WM, JV, YK, TS), pp. 433–447.
IJCAR-2010-BeierleFKT #automation #information management #reasoning #relational #representation: Automated Reasoning for Relational Probabilistic Knowledge Representation (CB, MF, GKI, MT), pp. 218–224.
LICS-2010-AlvimAP #data flow: Probabilistic Information Flow (MSA, MEA, CP), pp. 314–321.
LICS-2010-EisentrautHZ #automaton #on the: On Probabilistic Automata in Continuous Time (CE, HH, LZ), pp. 342–351.
LICS-2010-Goubault-Larrecq: ω-QRB-Domains and the Probabilistic Powerdomain (JGL), pp. 352–361.
SAT-2010-BalintF #satisfiability: Improving Stochastic Local Search for SAT with a New Probability Distribution (AB, AF), pp. 10–15.
VMCAI-2010-Esparza #analysis #process: Analysis of Systems with Stochastic Process Creation (JE), p. 1.
VMCAI-2010-Katoen #model checking #roadmap: Advances in Probabilistic Model Checking (JPK), p. 25.
VMCAI-2010-WachterZ: Best Probabilistic Transformers (BW, LZ), pp. 362–379.
ECDL-2009-StefaniNV #component #information management #modelling #visualisation: A Visualization Tool of Probabilistic Models for Information Access Components (LDS, GMDN, GV), pp. 481–482.
ICDAR-2009-HamamuraAI #recognition #word: An A Posteriori Probability Calculation Method for Analytic Word Recognition Applicable to Address Recognition (TH, TA, BI), pp. 391–395.
ICDAR-2009-KatayamaUS #order: Stochastic Model of Stroke Order Variation (YK, SU, HS), pp. 803–807.
ICDAR-2009-NatarajanSBP #modelling #recognition: Stochastic Segment Modeling for Offline Handwriting Recognition (PN, KS, AB, RP), pp. 971–975.
ICDAR-2009-ParakhinH #ranking: Finding the Most Probable Ranking of Objects with Probabilistic Pairwise Preferences (MP, PMH), pp. 616–620.
ICDAR-2009-ZhuGGZ #framework #learning #online #recognition: A Probabilistic Framework for Soft Target Learning in Online Cursive Handwriting Recognition (XZ, YG, FJG, LXZ), pp. 1246–1250.
PODS-2009-CohenKS #automaton #xml: Running tree automata on probabilistic XML (SC, BK, YS), pp. 227–236.
PODS-2009-LiD #database #query: Consensus answers for queries over probabilistic databases (JL, AD), pp. 259–268.
SIGMOD-2009-DalviBS #approach #robust #web: Robust web extraction: an approach based on a probabilistic tree-edit model (NND, PB, FS), pp. 335–348.
SIGMOD-2009-HuangAKO #database #named: MayBMS: a probabilistic database management system (JH, LA, CK, DO), pp. 1071–1074.
SIGMOD-2009-KanagalD #correlation #database: Indexing correlated probabilistic databases (BK, AD), pp. 455–468.
SIGMOD-2009-LiYJ #distributed #ranking: Ranking distributed probabilistic data (FL, KY, JJ), pp. 361–374.
VLDB-2009-CormodeDGM: Probabilistic Histograms for Probabilistic Data (GC, AD, MNG, AM), pp. 526–537.
VLDB-2009-LiSD #approach #database #ranking: A Unified Approach to Ranking in Probabilistic Databases (JL, BS, AD), pp. 502–513.
DLT-2009-BolligG #logic: Weighted versus Probabilistic Logics (BB, PG), pp. 18–38.
ICALP-v1-2009-HoyrupR #effectiveness: Applications of Effective Probability Theory to Martin-Löf Randomness (MH, CR), pp. 549–561.
ICALP-v2-2009-BouyerF #game studies #reachability: Reachability in Stochastic Timed Games (PB, VF), pp. 103–114.
ICALP-v2-2009-ChatterjeeDH #game studies #overview: A Survey of Stochastic Games with Limsup and Liminf Objectives (KC, LD, TAH), pp. 1–15.
ICALP-v2-2009-GriponS #concurrent #game studies: Qualitative Concurrent Stochastic Games with Imperfect Information (VG, OS), pp. 200–211.
ICALP-v2-2009-NicolaLLM #calculus #process: Rate-Based Transition Systems for Stochastic Process Calculi (RDN, DL, ML, MM), pp. 435–446.
ICALP-v2-2009-UmmelsW #complexity #game studies #multi #nash: The Complexity of Nash Equilibria in Simple Stochastic Multiplayer Games (MU, DW), pp. 297–308.
FM-2009-ChenS #nondeterminism: Unifying Probability with Nondeterminism (YC, JWS), pp. 467–482.
FM-2009-McIverMM #security: Security, Probability and Nearly Fair Coins in the Cryptographers’ Café (AM, LM, CM), pp. 41–71.
IFM-2009-HasanAT #analysis #array #configuration management #fault #memory management: Formal Probabilistic Analysis of Stuck-at Faults in Reconfigurable Memory Arrays (OH, NA, ST), pp. 277–291.
SEFM-2009-BertoliniM #model checking #testing #user interface #using: Using Probabilistic Model Checking to Evaluate GUI Testing Techniques (CB, AM), pp. 115–124.
DHM-2009-BurghardtK #approach #behaviour #modelling #smarttech: A Probabilistic Approach for Modeling Human Behavior in Smart Environments (CB, TK), pp. 202–210.
DHM-2009-MobusEGZ #empirical #modelling: Probabilistic and Empirical Grounded Modeling of Agents in (Partial) Cooperative Traffic Scenarios (CM, ME, HG, MZ), pp. 423–432.
ICEIS-J-2009-Cuzzocrea #approximate #evaluation #named #query #reduction #scalability: s-OLAP: Approximate OLAP Query Evaluation on Very Large Data Warehouses via Dimensionality Reduction and Probabilistic Synopses (AC), pp. 248–262.
ICEIS-SAIC-2009-ClariziaCSN #semantics #web: Semantic Indexing of Web Pages Via Probabilistic Methods — In Search of Semantics Project (FC, FC, MDS, PN), pp. 134–140.
CIKM-2009-BohmFOPW #query: Probabilistic skyline queries (CB, FF, AO, CP, BW), pp. 651–660.
CIKM-2009-CarteretteC #documentation #modelling #novel #ranking #retrieval #topic: Probabilistic models of ranking novel documents for faceted topic retrieval (BC, PC), pp. 1287–1296.
CIKM-2009-ChenLAA #image #learning #modelling #online #topic: Probabilistic models for topic learning from images and captions in online biomedical literatures (XC, CL, YA, PA), pp. 495–504.
CIKM-2009-GuYGC #data type #query: Probabilistic moving range query over RFID spatio-temporal data streams (YG, GY, NG, YC), pp. 1413–1416.
CIKM-2009-LiuZY #analysis #collaboration: Probabilistic latent preference analysis for collaborative filtering (NNL, MZ, QY), pp. 759–766.
CIKM-2009-WuB #predict: Predicting the conversion probability for items on C2C ecommerce sites (XW, AB), pp. 1377–1386.
CIKM-2009-YeCCZ #distributed: Stochastic gradient boosted distributed decision trees (JY, JHC, JC, ZZ), pp. 2061–2064.
CIKM-2009-YuLC #approach #information management: An integrated discriminative probabilistic approach to information extraction (XY, WL, BC), pp. 325–334.
ECIR-2009-KimXC #retrieval #semistructured data: A Probabilistic Retrieval Model for Semistructured Data (JK, XX, WBC), pp. 228–239.
ICML-2009-CaiWH #consistency #data analysis: Probabilistic dyadic data analysis with local and global consistency (DC, XW, XH), pp. 105–112.
ICML-2009-LangT #approximate #relational: Approximate inference for planning in stochastic relational worlds (TL, MT), pp. 585–592.
ICML-2009-RoyLW #consistency #learning #modelling #visual notation: Learning structurally consistent undirected probabilistic graphical models (SR, TL, MWW), pp. 905–912.
ICML-2009-Shalev-ShwartzT: Stochastic methods for l1 regularized loss minimization (SSS, AT), pp. 929–936.
ICML-2009-WoodAGJT #sequence: A stochastic memoizer for sequence data (FW, CA, JG, LJ, YWT), pp. 1129–1136.
ICML-2009-YiWSS #using: Stochastic search using the natural gradient (YS, DW, TS, JS), pp. 1161–1168.
KDD-2009-BerneckerKRVZ #database #mining #nondeterminism: Probabilistic frequent itemset mining in uncertain databases (TB, HPK, MR, FV, AZ), pp. 119–128.
KDD-2009-SatuluriP #clustering #community #graph #scalability #using: Scalable graph clustering using stochastic flows: applications to community discovery (VS, SP), pp. 737–746.
KDIR-2009-WangVH #documentation #retrieval #using: Document Retrieval using a Probabilistic Knowledge Model (SW, SV, MH), pp. 26–33.
KEOD-2009-Haddad #approach #representation #towards #word: Representation of Arabic Words — An Approach Towards Probabilistic Root-Pattern Relationships (BH), pp. 147–152.
MLDM-2009-BenabdeslemS #approach #clustering: A Probabilistic Approach for Constrained Clustering with Topological Map (KB, JS), pp. 413–426.
MLDM-2009-NikolopoulosPKP #comprehension #framework #image #semantics: An Evidence-Driven Probabilistic Inference Framework for Semantic Image Understanding (SN, GTP, IK, IP), pp. 525–539.
SIGIR-2009-LiLLL #framework #information retrieval #ranking #topic: A probabilistic topic-based ranking framework for location-sensitive domain information retrieval (HL, ZL, WCL, DLL), pp. 331–338.
SIGIR-2009-NaN #retrieval: A 2-poisson model for probabilistic coreference of named entities for improved text retrieval (SHN, HTN), pp. 275–282.
SIGIR-2009-Peng #analysis #equivalence #semantics: Equivalence between nonnegative tensor factorization and tensorial probabilistic latent semantic analysis (WP), pp. 668–669.
QAPL-2009-Bernardo #logic #markov #nondeterminism #process #testing: Uniform Logical Characterizations of Testing Equivalences for Nondeterministic, Probabilistic and Markovian Processes (MB), pp. 3–23.
QAPL-2009-GiroD #distributed #on the #power of: On the Expressive Power of Schedulers in Distributed Probabilistic Systems (SG, PRD), pp. 45–71.
QAPL-2009-LanevePZ #process: From Biochemistry to Stochastic Processes (CL, SP, GZ), pp. 167–185.
ASE-2009-ZhangGTL #sequence chart #syntax: A Formal Syntax for Probabilistic Timed Property Sequence Charts (PZ, LG, AT, BL), pp. 500–504.
ESEC-FSE-2009-GrunskeZ #monitoring: Monitoring probabilistic properties (LG, PZ), pp. 183–192.
ESEC-FSE-2009-MaiaKUM #modelling #refinement #towards #using: Towards accurate probabilistic models using state refinement (PHMM, JK, SU, NCM), pp. 281–284.
ESEC-FSE-2009-PaveseBU #analysis #behaviour #modelling: Probabilistic environments in the quantitative analysis of (non-probabilistic) behaviour models (EP, VAB, SU), pp. 335–344.
ICSE-2009-MenziesWBH #how #process #using: How to avoid drastic software process change (using stochastic stability) (TM, SW, BWB, JH), pp. 540–550.
SAC-2009-CasadeiV #design #model checking #self #simulation #using: Using probabilistic model checking and simulation for designing self-organizing systems (MC, MV), pp. 2103–2104.
SAC-2009-CipciganR #difference #equation: Interlaced Euler scheme for stiff systems of stochastic differential equations (IC, MR), pp. 989–994.
SAC-2009-GiroD #automaton #on the #verification: On the verification of probabilistic I/O automata with unspecified rates (SG, PRD), pp. 582–586.
SAC-2009-KangCRRV #adaptation #composition #implementation #simulation: Modular implementation of adaptive decisions in stochastic simulations (PK, YC, NR, CJR, SV), pp. 995–1001.
SAC-2009-LeccaPPS #generative #network #parametricity: A new probabilistic generative model of parameter inference in biochemical networks (PL, AP, CP, GS), pp. 758–765.
SAC-2009-LiuMYGF #corpus #mining: A sentence level probabilistic model for evolutionary theme pattern mining from news corpora (SL, YM, WGY, NG, OF), pp. 1742–1747.
CASE-2009-ZiedSN #maintenance #random: An optimal production/maintenance planning under stochastic random demand, service level and failure rate (ZH, SD, NR), pp. 292–297.
DAC-2009-BurnhamYH: A stochastic jitter model for analyzing digital timing-recovery circuits (JRB, CKKY, HAH), pp. 116–121.
DAC-2009-GongYH #incremental #named #parallel #process: PiCAP: a parallel and incremental capacitance extraction considering stochastic process variation (FG, HY, LH), pp. 764–769.
DAC-2009-KimRH #analysis: Stochastic steady-state and AC analyses of mixed-signal systems (JK, JR, MAH), pp. 376–381.
HPCA-2009-HurL #feedback #memory management: Feedback mechanisms for improving probabilistic memory prefetching (IH, CL), pp. 443–454.
SOSP-2009-ParkZXYKLL #execution #multi #named #sketching: PRES: probabilistic replay with execution sketching on multiprocessors (SP, YZ, WX, ZY, RK, KHL, SL), pp. 177–192.
FoSSaCS-2009-AbbesB #algebra #concurrent: Concurrency, σ-Algebras, and Probabilistic Fairness (SA, AB), pp. 380–394.
STOC-2009-GuptaK #approximate: A constant-factor approximation for stochastic Steiner forest (AG, AK), pp. 659–668.
STOC-2009-GuptaKR #design #network #online: Online and stochastic survivable network design (AG, RK, RR), pp. 685–694.
CSL-2009-UmmelsW #game studies #nash #problem: Decision Problems for Nash Equilibria in Stochastic Games (MU, DW), pp. 515–529.
ICLP-2009-BroechelerSS #logic programming #query #source code #using: Using Histograms to Better Answer Queries to Probabilistic Logic Programs (MB, GIS, VSS), pp. 40–54.
ICLP-2009-Raedt #learning #logic #tutorial: Probabilistic Logic Learning — A Tutorial Abstract (LDR), p. 39.
ICLP-2009-Simari #behaviour #modelling #reasoning: Stochastic Reasoning with Models of Agent Behavior (GIS), pp. 538–539.
ICST-2009-AndresMN #testing: Passive Testing of Stochastic Timed Systems (CA, MGM, MN), pp. 71–80.
LICS-2009-BertrandGG #decidability #game studies: Qualitative Determinacy and Decidability of Stochastic Games with Signals (NB, BG, HG), pp. 319–328.
LICS-2009-RougemontT #analysis #process #statistics: Statistic Analysis for Probabilistic Processes (MdR, MT), pp. 299–308.
SAT-2009-BelovS #process #satisfiability: Improving Variable Selection Process in Stochastic Local Search for Propositional Satisfiability (AB, ZS), pp. 258–264.
SAT-2009-HsuM #named #novel: VARSAT: Integrating Novel Probabilistic Inference Techniques with DPLL Search (EIH, SAM), pp. 377–390.
VMCAI-2009-GondiPS #monitoring: Monitoring the Full Range of omega-Regular Properties of Stochastic Systems (KG, YP, APS), pp. 105–119.
VMCAI-2009-KattenbeltKNP #abstraction #refinement: Abstraction Refinement for Probabilistic Software (MK, MZK, GN, DP), pp. 182–197.
QoSA-2008-GallottiGMT #composition #model checking #predict #quality: Quality Prediction of Service Compositions through Probabilistic Model Checking (SG, CG, RM, GT), pp. 119–134.
PODS-2008-CohenKS #constraints #xml: Incorporating constraints in probabilistic XML (SC, BK, YS), pp. 109–118.
PODS-2008-Koch #approximate #database #query: Approximating predicates and expressive queries on probabilistic databases (CK), pp. 99–108.
SIGMOD-2008-HuaPZL #approach #nondeterminism #query #ranking: Ranking queries on uncertain data: a probabilistic threshold approach (MH, JP, WZ, XL), pp. 673–686.
SIGMOD-2008-KimelfeldKS #modelling #performance #query #xml: Query efficiency in probabilistic XML models (BK, YK, YS), pp. 701–714.
SIGMOD-2008-PeiHTL #nondeterminism #query #summary #tutorial: Query answering techniques on uncertain and probabilistic data: tutorial summary (JP, MH, YT, XL), pp. 1357–1364.
SIGMOD-2008-ReLBS #correlation #query: Event queries on correlated probabilistic streams (CR, JL, MB, DS), pp. 715–728.
SIGMOD-2008-ZhangLY: Finding frequent items in probabilistic data (QZ, FL, KY), pp. 819–832.
VLDB-2008-BalazinskaRS #aspect-oriented #data transformation: Systems aspects of probabilistic data management (MB, CR, DS), pp. 1520–1521.
VLDB-2008-KochO #database: Conditioning probabilistic databases (CK, DO), pp. 313–325.
VLDB-2008-ReS #approximate #database: Approximate lineage for probabilistic databases (CR, DS), pp. 797–808.
VLDB-2008-SenDG #correlation #database: Exploiting shared correlations in probabilistic databases (PS, AD, LG), pp. 809–820.
VLDB-2008-WangMGH #modelling #named #nondeterminism #repository #scalability #visual notation: BayesStore: managing large, uncertain data repositories with probabilistic graphical models (DZW, EM, MNG, JMH), pp. 340–351.
DLT-J-2007-Freivalds08 #automaton #finite: Non-Constructive Methods for Finite Probabilistic Automata (RF), pp. 565–580.
CIAA-2008-Yannakakis #automaton #recursion: Automata, Probability, and Recursion (MY), pp. 23–32.
ICALP-A-2008-EtessamiWY #game studies #recursion: Recursive Stochastic Games with Positive Rewards (KE, DW, MY), pp. 711–723.
LATA-2008-RegnaultST #2d #analysis #automaton #on the: On the Analysis of “Simple” 2D Stochastic Cellular Automata (DR, NS, ET), pp. 452–463.
FM-2008-McIverMG #proving #refinement: Proofs and Refutations for Probabilistic Refinement (AKM, CCM, CG), pp. 100–115.
SFM-2008-DegasperiG #analysis #modelling: Sensitivity Analysis of Stochastic Models of Bistable Biochemical Reactions (AD, SG), pp. 1–20.
SFM-2008-Zavattaro #automaton: A Gentle Introduction to Stochastic (Poly)Automata Collectives and the (Bio)Chemical Ground Form (GZ), pp. 507–523.
AIIDE-2008-TrustyOR #game studies #optimisation #realtime: Stochastic Plan Optimization in Real-Time Strategy Games (AT, SO, AR).
CIG-2008-OsakiSTK #difference #evaluation #learning #using: An Othello evaluation function based on Temporal Difference Learning using probability of winning (YO, KS, YT, YK), pp. 205–211.
CAiSE-2008-IoannouNN: Probabilistic Entity Linkage for Heterogeneous Information Spaces (EI, CN, WN), pp. 556–570.
CIKM-2008-BoedihardjoLC #data type #framework: A framework for estimating complex probability density structures in data streams (APB, CTL, FC), pp. 619–628.
CIKM-2008-ChiZGZ #personalisation #recommendation: Probabilistic polyadic factorization and its application to personalized recommendation (YC, SZ, YG, YZ), pp. 941–950.
CIKM-2008-ChungLC #performance #query: Efficient processing of probabilistic spatio-temporal range queries over moving objects (BSEC, WCL, ALPC), pp. 1399–1400.
CIKM-2008-MaYLK08a #matrix #named #recommendation #social #using: SoRec: social recommendation using probabilistic matrix factorization (HM, HY, MRL, IK), pp. 931–940.
ECIR-2008-BlancoB #documentation #modelling: Probabilistic Document Length Priors for Language Models (RB, AB), pp. 394–405.
ECIR-2008-LillisTCD #data fusion #using: Extending Probabilistic Data Fusion Using Sliding Windows (DL, FT, RWC, JD), pp. 358–369.
ECIR-2008-NaKL08c #similarity #using: Query-Based Inter-document Similarity Using Probabilistic Co-relevance Model (SHN, ISK, JHL), pp. 684–688.
ICML-2008-OBrienGG #classification #multi: Cost-sensitive multi-class classification from probability estimates (DBO, MRG, RMG), pp. 712–719.
ICML-2008-SalakhutdinovM08a #markov #matrix #monte carlo #using: Bayesian probabilistic matrix factorization using Markov chain Monte Carlo (RS, AM), pp. 880–887.
ICML-2008-SokolovskaCY #learning #modelling: The asymptotics of semi-supervised learning in discriminative probabilistic models (NS, OC, FY), pp. 984–991.
ICPR-2008-Bauckhage #classification #detection: Probabilistic Diffusion Classifiers for Object Detection (CB), pp. 1–4.
ICPR-2008-BorsN #estimation #kernel #modelling: Kernel bandwidth estimation in methods based on probability density function modelling (AGB, NN), pp. 1–4.
ICPR-2008-DingB08a #difference #recognition: Probabilistic mixtures of differential profiles for shape recognition (LD, MB), pp. 1–4.
ICPR-2008-DonoserMBK #approach: A probabilistic approach for tracking fibers (MD, TM, HB, JK), pp. 1–4.
ICPR-2008-KimuraPTYK #markov #modelling #random #visual notation: Dynamic Markov random fields for stochastic modeling of visual attention (AK, DP, TT, JY, KK), pp. 1–5.
ICPR-2008-LefebvreG #recognition #self: A probabilistic Self-Organizing Map for facial recognition (GL, CG), pp. 1–4.
ICPR-2008-LevadaMT #image #markov #modelling #on the #random: On the asymptotic variances of Gaussian Markov Random Field model hyperparameters in stochastic image modeling (ALML, NDAM, AT), pp. 1–4.
ICPR-2008-LiLWLD #sketching: Object-of-interest extraction by integrating stochastic inference with learnt active shape sketch (HL, LL, TW, XL, LD), pp. 1–4.
ICPR-2008-LiuLLJT #graph #representation: Layered shape matching and registration: Stochastic sampling with hierarchical graph representation (XL, LL, HL, HJ, WT), pp. 1–4.
ICPR-2008-LouJ #distance #image #recognition: Integrated probability function on local mean distance for image recognition (ZL, ZJ), pp. 1–4.
ICPR-2008-Patanavijit #estimation #multi #robust: A robust iterative multiframe SRR based on Hampel stochastic estimation with Hampel-Tikhonov regularization (VP), pp. 1–4.
ICPR-2008-TranTJ #anti #linear #network: An adjustable combination of linear regression and modified probabilistic neural network for anti-spam filtering (TPT, PT, TJ), pp. 1–4.
ICPR-2008-WangM #invariant #recognition #similarity #using: Scale invariant face recognition using probabilistic similarity measure (ZW, ZM), pp. 1–4.
ICPR-2008-WetzkerPKBAM #detection #generative #roadmap #social #using: Detecting trends in social bookmarking systems using a probabilistic generative model and smoothing (RW, TP, AK, CB, TA, FM), pp. 1–4.
ICPR-2008-WooKK: Probabilistic matching of line segments for their homography (JW, TK, ISK), pp. 1–4.
ICPR-2008-WuNC #image: A probabilistic model for classifying segmented images (LW, PN, LNC), pp. 1–4.
ICPR-2008-WuWLL: Probabilistic tracking on Riemannian manifolds (YW, BW, JL, HL), pp. 1–4.
ICPR-2008-YamaguchiM #categorisation #classification #image #topic: Image categorization by a classifier based on probabilistic topic model (TY, MM), pp. 1–4.
ICPR-2008-YaoCAPKA #using: Sensor planning for PTZ cameras using the probability of camera overload (YY, CHC, BRA, DLP, AK, MAA), pp. 1–5.
KDD-2008-IwataYU #documentation #semantics #topic #visualisation: Probabilistic latent semantic visualization: topic model for visualizing documents (TI, TY, NU), pp. 363–371.
RecSys-2008-WuWC #analysis #automation #incremental #recommendation #semantics: Incremental probabilistic latent semantic analysis for automatic question recommendation (HW, YW, XC), pp. 99–106.
SEKE-2008-ParveenATMF #analysis #detection #towards: Towards the Detection of Emulated Environments via Analysis of the Stochastic Nature of System Calls (TP, WHA, SRT, GAM, RF), pp. 802–807.
SIGIR-2008-DingLLP #clustering #using: Posterior probabilistic clustering using NMF (CHQD, TL, DL, WP), pp. 831–832.
SIGIR-2008-WangS #modelling #retrieval: Discriminative probabilistic models for passage based retrieval (MW, LS), pp. 419–426.
SIGIR-2008-XuA08a #modelling #multi #retrieval: A new probabilistic retrieval model based on the dirichlet compound multinomial distribution (ZX, RA), pp. 427–434.
QAPL-2008-Bortolussi #approximate #concurrent #constraints #equation #on the #programming: On the Approximation of Stochastic Concurrent Constraint Programming by Master Equation (LB), pp. 163–180.
QAPL-2008-KattenbeltKNP #abstraction #game studies: Game-Based Probabilistic Predicate Abstraction in PRISM (MK, MZK, GN, DP), pp. 5–21.
QAPL-2008-PierroSW #abstract interpretation #analysis #precise #relational: Relational Analysis and Precision via Probabilistic Abstract Interpretation (ADP, PS, HW), pp. 23–42.
QAPL-2008-Smith #abstract interpretation #imperative #source code #using: Probabilistic Abstract Interpretation of Imperative Programs using Truncated Normal Distributions (MJAS), pp. 43–59.
QAPL-2008-TrckaG #bisimulation #branch #congruence: Branching Bisimulation Congruence for Probabilistic Systems (NT, SG), pp. 129–143.
QAPL-2008-TzanisH #logic: Probabilistic Logic over Paths (ET, RH), pp. 79–96.
ICSE-2008-Grunske #quality #specification: Specification patterns for probabilistic quality properties (LG), pp. 31–40.
SAC-2008-CasimiroLDBV #adaptation #framework: A framework for dependable QoS adaptation in probabilistic environments (AC, PL, MD, AB, PV), pp. 2192–2196.
SAC-2008-HojjatMS #algebra #evaluation #framework #functional #performance #process #verification: A framework for performance evaluation and functional verification in stochastic process algebras (HH, MRM, MS), pp. 339–346.
SAC-2008-TakasuA #analysis #documentation #information management #layout: Information extraction from scanned documents by stochastic page layout analysis (AT, KA), pp. 447–448.
CASE-2008-AdamekSS #hybrid #nondeterminism: Stochastic optimal control for hybrid systems with uncertain discrete dynamics (FA, MS, OS), pp. 23–28.
CASE-2008-BrantleyLCC #design #empirical #optimisation: Optimal sampling in design of experiment for simulation-based stochastic optimization (MWB, LHL, CHC, AC), pp. 388–393.
CASE-2008-MittalYBB #difference #equation #modelling #multi #performance #using: Dynamics and performance modeling of multi-stage manufacturing systems using nonlinear stochastic differential equations (UM, HY, STSB, LGB), pp. 498–503.
DAC-2008-JungRP #manycore #modelling: Stochastic modeling of a thermally-managed multi-core system (HJ, PR, MP), pp. 728–733.
DAC-2008-LiangM #analysis #execution #modelling: Cache modeling in probabilistic execution time analysis (YL, TM), pp. 319–324.
DAC-2008-LiASR #array #design #memory management #modelling #random #statistics: Modeling of failure probability and statistical design of spin-torque transfer magnetic random access memory (STT MRAM) array for yield enhancement (JL, CA, SSS, KR), pp. 278–283.
DAC-2008-MoselhyD #equation #performance: Stochastic integral equation solver for efficient variation-aware interconnect extraction (TM, LD), pp. 415–420.
DAC-2008-QianR #logic #polynomial #robust #synthesis: The synthesis of robust polynomial arithmetic with stochastic logic (WQ, MDR), pp. 648–653.
DATE-2008-Liu #analysis #statistics: Signal Probability Based Statistical Timing Analysis (BL), pp. 562–567.
DATE-2008-TanQ #framework #markov #power management #using: A Framework of Stochastic Power Management Using Hidden Markov Model (YT, QQ), pp. 92–97.
PDP-2008-ColmenarMGLH #modelling #using: Modelling Asynchronous Systems using Probability Distribution Functions (JMC, NM, OG, JL, JIH), pp. 3–11.
PPoPP-2008-NurmiWB #parallel: Probabilistic advanced reservations for batch-scheduled parallel machines (DN, RW, JB), pp. 289–290.
FoSSaCS-2008-AbdullaHAMS #game studies: Stochastic Games with Lossy Channels (PAA, NBH, LdA, RM, SS), pp. 35–49.
FoSSaCS-2008-BaierBG #automaton #on the #problem: On Decision Problems for Probabilistic Büchi Automata (CB, NB, MG), pp. 287–301.
FoSSaCS-2008-GimbertH #game studies #random: Simple Stochastic Games with Few Random Vertices Are Easy to Solve (HG, FH), pp. 5–19.
FoSSaCS-2008-Goubault-Larrecq #game studies #infinity #simulation: Simulation Hemi-metrics between Infinite-State Stochastic Games (JGL), pp. 50–65.
FoSSaCS-2008-KlinS #calculus #process #semantics: Structural Operational Semantics for Stochastic Process Calculi (BK, VS), pp. 428–442.
TACAS-2008-AndresR #nondeterminism: Conditional Probabilities over Probabilistic and Nondeterministic Systems (MEA, PvR), pp. 157–172.
TACAS-2008-LegayMOW #automation #on the #source code #verification: On Automated Verification of Probabilistic Programs (AL, ASM, JO, JW), pp. 173–187.
CAV-2008-HermannsWZ: Probabilistic CEGAR (HH, BW, LZ), pp. 162–175.
ICLP-2008-ArandaPRV #behaviour #concurrent #constraints #programming: Stochastic Behavior and Explicit Discrete Time in Concurrent Constraint Programming (JA, JAP, CR, FDV), pp. 682–686.
ICLP-2008-Beauxis #concurrent #modelling #security: Probabilistic and Concurrent Models for Security (RB), pp. 801–802.
ISSTA-2008-BaahPH #dependence #fault #graph: The probabilistic program dependence graph and its application to fault diagnosis (GKB, AP, MJH), pp. 189–200.
LICS-2008-BrazdilFKK #problem #satisfiability: The Satisfiability Problem for Probabilistic CTL (TB, VF, JK, AK), pp. 391–402.
VMCAI-2008-SistlaS #monitoring: Monitoring Temporal Properties of Stochastic Systems (APS, ARS), pp. 294–308.
ECDL-2007-Frommholz #documentation #logic #retrieval: Annotation-Based Document Retrieval with Probabilistic Logics (IF), pp. 321–332.
ICDAR-2007-HamamuraAI #algorithm #recognition #using #word: An Analytic Word Recognition Algorithm Using a Posteriori Probability (TH, TA, BI), pp. 669–673.
ICDAR-2007-KramerKKB #finite #metadata #transducer #using: Bibliographic Meta-Data Extraction Using Probabilistic Finite State Transducers (MK, HK, DK, TMB), pp. 609–613.
PODS-2007-DalviS #challenge: Management of probabilistic data: foundations and challenges (NND, DS), pp. 1–12.
PODS-2007-DalviS07a #query: The dichotomy of conjunctive queries on probabilistic structures (NND, DS), pp. 293–302.
PODS-2007-JayramMMV #data type #statistics: Estimating statistical aggregates on probabilistic data streams (TSJ, AM, SM, EV), pp. 243–252.
PODS-2007-KimelfeldS: Maximally joining probabilistic data (BK, YS), pp. 303–312.
PODS-2007-SenellartA #complexity #on the #xml: On the complexity of managing probabilistic XML data (PS, SA), pp. 283–292.
SIGMOD-2007-BravoR #optimisation #query: Optimizing mpf queries: decision support and probabilistic inference (HCB, RR), pp. 701–712.
SIGMOD-2007-CormodeG #data type #sketching: Sketching probabilistic data streams (GC, MNG), pp. 281–292.
VLDB-2007-DeshpandeS #database #modelling #visual notation: Probabilistic Graphical Models and their Role in Databases (AD, SS), pp. 1435–1436.
VLDB-2007-KimelfeldS #xml: Matching Twigs in Probabilistic XML (BK, YS), pp. 27–38.
VLDB-2007-PeiJLY #nondeterminism: Probabilistic Skylines on Uncertain Data (JP, BJ, XL, YY), pp. 15–26.
VLDB-2007-ReS #database #optimisation #query: Materialized Views in Probabilistic Databases for Information Exchange and Query Optimization (CR, DS), pp. 51–62.
CSMR-2007-SharafatT #approach #object-oriented #predict: A Probabilistic Approach to Predict Changes in Object-Oriented Software Systems (ARS, LT), pp. 27–38.
ICSM-2007-McMasterM #analysis #detection #fault #reduction #testing: Fault Detection Probability Analysis for Coverage-Based Test Suite Reduction (SM, AMM), pp. 335–344.
CIAA-J-2006-CortesMR07 #automaton #distance #equivalence: LP Distance and Equivalence of Probabilistic Automata (CC, MM, AR), pp. 761–779.
DLT-2007-Freivalds #automaton #finite: Non-constructive Methods for Finite Probabilistic Automata (RF), pp. 169–180.
ICALP-2007-GimbertZ #game studies: Perfect Information Stochastic Priority Games (HG, WZ), pp. 850–861.
ICALP-2007-KatrielKU #nondeterminism #problem: Commitment Under Uncertainty: Two-Stage Stochastic Matching Problems (IK, CKM, EU), pp. 171–182.
IFM-2007-ColvinGW #behaviour: Probabilistic Timed Behavior Trees (RC, LG, KW), pp. 156–175.
IFM-2007-HallerstedeH #modelling: Qualitative Probabilistic Modelling in Event-B (SH, TSH), pp. 293–312.
IFM-2007-HasanT #cumulative #using #verification: Verification of Probabilistic Properties in HOL Using the Cumulative Distribution Function (OH, ST), pp. 333–352.
SEFM-2007-MerayoN #consistency #testing: Testing conformance on Stochastic Stream X-Machines (MGM, MN), pp. 227–236.
SFM-2007-Balbo #petri net: Introduction to Generalized Stochastic Petri Nets (GB), pp. 83–131.
SFM-2007-ClarkGHT #algebra #process: Stochastic Process Algebras (AC, SG, JH, MT), pp. 132–179.
SFM-2007-KwiatkowskaNP #model checking: Stochastic Model Checking (MZK, GN, DP), pp. 220–270.
CIG-2007-OommenGP #bound #finite #game studies #using: Using Stochastic AI Techniques to Achieve Unbounded Resolution in Finite Player Goore Games and its Applications (BJO, OCG, AP), pp. 161–167.
CIG-2007-VenessB #effectiveness #game studies #using: Effective Use of Transposition Tables in Stochastic Game Tree Search (JV, AB), pp. 112–116.
HCI-IPT-2007-KellenCF #problem: Facilitating Conditional Probability Problems with Visuals (VK, SSC, XF), pp. 63–71.
HIMI-MTT-2007-ChoBKC #difference #on the #using: On Achieving Proportional Loss Differentiation Using Dynamic-MQDDP with Differential Drop Probability (KC, SB, JK, JWC), pp. 584–593.
CIKM-2007-BacheBC #modelling: Language models, probability of relevance and relevance likelihood (RB, MB, FC), pp. 853–856.
CIKM-2007-HeO #ad hoc #parametricity #retrieval: Parameter sensitivity in the probabilistic model for ad-hoc retrieval (BH, IO), pp. 263–272.
CIKM-2007-SongC #similarity: Probabilistic correlation-based similarity measure of unstructured records (SS, LC), pp. 967–970.
CIKM-2007-YanH #feedback #multi #query #retrieval #using: Query expansion using probabilistic local feedback with application to multimedia retrieval (RY, AGH), pp. 361–370.
CIKM-2007-ZhangTLW #ambiguity #constraints #framework: A constraint-based probabilistic framework for name disambiguation (DZ, JT, JZL, KW), pp. 1019–1022.
ECIR-2007-FangZ #modelling: Probabilistic Models for Expert Finding (HF, CZ), pp. 418–430.
ECIR-2007-ZhuTZM #clustering #documentation #multi: A Probabilistic Model for Clustering Text Documents with Multiple Fields (SZ, IT, SZ, HM), pp. 331–342.
ICML-2007-HeraultG #classification: Sparse probabilistic classifiers (RH, YG), pp. 337–344.
ICML-2007-McNeillV #generative #linear #modelling: Linear and nonlinear generative probabilistic class models for shape contours (GM, SV), pp. 617–624.
ICML-2007-NelsonC #clustering #constraints #modelling: Revisiting probabilistic models for clustering with pair-wise constraints (BN, IC), pp. 673–680.
KDD-2007-CotofreiS #data mining #mining #process: Stochastic processes and temporal data mining (PC, KS), pp. 183–190.
KDD-2007-LongZY #clustering #framework #relational: A probabilistic framework for relational clustering (BL, Z(Z, PSY), pp. 470–479.
KDD-2007-Sandler #analysis #modelling: Hierarchical mixture models: a probabilistic analysis (MS), pp. 580–589.
MLDM-2007-TanN #data mining #mining #privacy #re-engineering: Generic Probability Density Function Reconstruction for Randomization in Privacy-Preserving Data Mining (VYFT, SKN), pp. 76–90.
MLDM-2007-WisniewskiMDG #documentation: Probabilistic Model for Structured Document Mapping (GW, FM, LD, PG), pp. 854–867.
RecSys-2007-LiDEL #recommendation: A probabilistic model for item-based recommender systems (ML, MBD, WED, PJGL), pp. 129–132.
SEKE-2007-AlencarRSF #classification #modelling #project management: Combining Decorated Classification Trees with RCPS Stochastic Models to Gain New Valuable Insights into Software Project Management (AJA, GGR, EAS, ALF), pp. 151–156.
SIGIR-2007-KoNS #ranking #visual notation: A probabilistic graphical model for joint answer ranking in question answering (JK, EN, LS), pp. 343–350.
SIGIR-2007-Lee: IDF revisited: a simple new derivation within the Robertson-Spärck Jones probabilistic model (LL), pp. 751–752.
SIGIR-2007-WuLW #rank #ranking: Probability ranking principle via optimal expected rank (HCW, RWPL, KFW), pp. 713–714.
OOPSLA-2007-BondM: Probabilistic calling context (MDB, KSM), pp. 97–112.
PLDI-2007-NovarkBZ #automation #fault #memory management #named: Exterminator: automatically correcting memory errors with high probability (GN, EDB, BGZ), pp. 1–11.
POPL-2007-GulwaniJ #verification: Program verification as probabilistic inference (SG, NJ), pp. 277–289.
QAPL-2007-BaltazarMNP #logic: Exogenous Probabilistic Computation Tree Logic (PB, PM, RN, NP), pp. 95–110.
QAPL-2007-BortolussiP #concurrent #constraints #difference #equation #programming: Stochastic Concurrent Constraint Programming and Differential Equations (LB, AP), pp. 27–42.
QAPL-2007-DengD #congruence: Probabilistic Barbed Congruence (YD, WD), pp. 185–203.
QAPL-2007-PierroHW #analysis #data flow #on the: On Probabilistic Techniques for Data Flow Analysis (ADP, CH, HW), pp. 59–77.
QAPL-2007-Smith #communication #modelling #protocol #source code: Stochastic Modelling of Communication Protocols from Source Code (MJAS), pp. 129–145.
QAPL-2007-VaraccaY #π-calculus: Probabilistic π-Calculus and Event Structures (DV, NY), pp. 147–166.
ASE-2007-LinsteadRBLB #concept #mining #modelling #topic: Mining concepts from code with probabilistic topic models (EL, PR, SKB, CVL, PB), pp. 461–464.
SAC-2007-BordeauxS #constraints #framework #on the: On the stochastic constraint satisfaction framework (LB, HS), pp. 316–320.
CASE-2007-DingAS #modelling: Stochastic Modeling for Serial-Batching Workstations with Heterogeneous Machines (SD, RAT, JGS), pp. 77–81.
CASE-2007-DingSA #modelling: Stochastic Modeling for Serial-Batching Workstations with Heterogeneous Machines (SD, JGS, RAT), p. 91–?.
DAC-2007-KumarMCTH #approach #estimation #multi #performance: A Probabilistic Approach to Model Resource Contention for Performance Estimation of Multi-featured Media Devices (AK, BM, HC, BDT, YH), pp. 726–731.
DATE-2007-QiuTW #modelling #optimisation #power management #robust: Stochastic modeling and optimization for robust power management in a partially observable system (QQ, YT, QW), pp. 779–784.
DATE-2007-ZhuP #algorithm #graph #random: Random sampling of moment graph: a stochastic Krylov-reduction algorithm (ZZ, JRP), pp. 1502–1507.
DATE-2007-ZhuZCXZ #grid #process: A sparse grid based spectral stochastic collocation method for variations-aware capacitance extraction of interconnects under nanometer process technology (HZ, XZ, WC, JX, DZ), pp. 1514–1519.
ESOP-2007-DengGMZ #testing: Scalar Outcomes Suffice for Finitary Probabilistic Testing (YD, RJvG, CM, CZ), pp. 363–378.
ESOP-2007-HasuoK #algebra #simulation: Probabilistic Anonymity Via Coalgebraic Simulations (IH, YK), pp. 379–394.
FoSSaCS-2007-BreugelSW #approximate #behaviour #pseudo: Approximating a Behavioural Pseudometric Without Discount for Probabilistic Systems (FvB, BS, JW), pp. 123–137.
FoSSaCS-2007-Chatterjee #game studies #synthesis: Optimal Strategy Synthesis in Stochastic Müller Games (KC), pp. 138–152.
FoSSaCS-2007-ParmaS #bisimulation #logic: Logical Characterizations of Bisimulations for Discrete Probabilistic Systems (AP, RS), pp. 287–301.
TACAS-2007-HanK #model checking: Counterexamples in Probabilistic Model Checking (TH, JPK), pp. 72–86.
TACAS-2007-JurdzinskiLS #automaton #model checking: Model Checking Probabilistic Timed Automata with One or Two Clocks (MJ, FL, JS), pp. 170–184.
TACAS-2007-KatoenKZJ #bisimulation #model checking: Bisimulation Minimisation Mostly Speeds Up Probabilistic Model Checking (JPK, TK, ISZ, DNJ), pp. 87–101.
TACAS-2007-ZhangHEJ #algorithm #performance #simulation: Flow Faster: Efficient Decision Algorithms for Probabilistic Simulations (LZ, HH, FE, DNJ), pp. 155–169.
CADE-2007-HasanT #formal method: Formalization of Continuous Probability Distributions (OH, ST), pp. 3–18.
ICLP-2007-CaliL #logic programming #semantics #source code #web: Tightly Integrated Probabilistic Description Logic Programs for the Semantic Web (AC, TL), pp. 428–429.
LICS-2007-DengGHMZ #finite #process #testing: Characterising Testing Preorders for Finite Probabilistic Processes (YD, RJvG, MH, CM, CZ), pp. 313–325.
JCDL-2006-FrommholzF #library #logic #object-oriented #retrieval: Probabilistic, object-oriented logics for annotation-based retrieval in digital libraries (IF, NF), pp. 55–64.
VLDB-2006-GuptaS #database #information management #modelling: Creating Probabilistic Databases from Information Extraction Models (RG, SS), pp. 965–976.
ICPC-2006-PoshyvanykMRGA #identification #ranking #semantics: Combining Probabilistic Ranking and Latent Semantic Indexing for Feature Identification (DP, AM, VR, YGG, GA), pp. 137–148.
MSR-2006-WalkerHHKS #approach #estimation #impact analysis #lightweight: A lightweight approach to technical risk estimation via probabilistic impact analysis (RJW, RH, IH, PK, AS), pp. 98–104.
CIAA-2006-CortesMR #automaton #on the #standard: On the Computation of Some Standard Distances Between Probabilistic Automata (CC, MM, AR), pp. 137–149.
DLT-2006-Ravikumar #automaton #finite #modelling #on the: On Some Variations of Two-Way Probabilistic Finite Automata Models (BR), pp. 443–454.
ICALP-v2-2006-CorinH #encryption #game studies #hoare #logic #proving: A Probabilistic Hoare-style Logic for Game-Based Cryptographic Proofs (RC, JdH), pp. 252–263.
ICALP-v2-2006-EtessamiY #concurrent #game studies #recursion: Recursive Concurrent Stochastic Games (KE, MY), pp. 324–335.
FM-2006-McIver #analysis #model checking #refinement: Quantitative Refinement and Model Checking for the Analysis of Probabilistic Systems (AM), pp. 131–146.
ICGT-2006-MendizabalD #analysis #distributed #graph grammar #non-functional #using: Non-functional Analysis of Distributed Systems in Unreliable Environments Using Stochastic Object Based Graph Grammars (OMM, FLD), pp. 275–290.
CIKM-2006-LiSC #database #named #xml: PEPX: a query-friendly probabilistic XML database (TL, QS, YC), pp. 848–849.
CIKM-2006-ShakeryZ #hypermedia #retrieval: A probabilistic relevance propagation model for hypertext retrieval (AS, CZ), pp. 550–558.
CIKM-2006-WuLWK #feedback: Probabilistic document-context based relevance feedback with limited relevance judgments (HCW, RWPL, KFW, KLK), pp. 854–855.
ECIR-2006-FernandezVC #normalisation #rank: Probabilistic Score Normalization for Rank Aggregation (MF, DV, PC), pp. 553–556.
ICML-2006-ArchambeauDV #robust: Robust probabilistic projections (CA, ND, MV), pp. 33–40.
ICML-2006-LehmannS #kernel: A probabilistic model for text kernels (ADL, JST), pp. 537–544.
ICML-2006-RudaryS #modelling #predict: Predictive linear-Gaussian models of controlled stochastic dynamical systems (MRR, SPS), pp. 777–784.
ICML-2006-ToussaintS #markov #process: Probabilistic inference for solving discrete and continuous state Markov Decision Processes (MT, AJS), pp. 945–952.
ICML-2006-VishwanathanSSM #random: Accelerated training of conditional random fields with stochastic gradient methods (SVNV, NNS, MWS, KPM), pp. 969–976.
ICML-2006-WingateS #kernel #linear #modelling #predict: Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems (DW, SPS), pp. 1017–1024.
ICPR-v1-2006-LiL: Probabilistic Image-Based Rendering with Gaussian Mixture Model (WL, BL), pp. 179–182.
ICPR-v1-2006-TongJ #multi: Multiview Facial Feature Tracking with a Multi-modal Probabilistic Model (YT, QJ), pp. 307–310.
ICPR-v1-2006-YanCK #algorithm #video: A Maximum A Posteriori Probability Viterbi Data Association Algorithm for Ball Tracking in Sports Video (FY, WJC, JK), pp. 279–282.
ICPR-v2-2006-McNeillV: Part-Based Probabilistic Point Matching (GM, SV), pp. 382–386.
ICPR-v2-2006-MeleMS #categorisation #image #using: Image Categorization Using Local Probabilistic Descriptors (KM, JM, DS), pp. 336–340.
ICPR-v2-2006-MitaKH #approach #categorisation #performance #robust: A Probabilistic Approach to Fast and Robust Template Matching and its Application to Object Categorization (TM, TK, OH), pp. 597–601.
ICPR-v2-2006-PriorW #fault #parametricity #random #using: Parameter Tuning using the Out-of-Bootstrap Generalisation Error Estimate for Stochastic Discrimination and Random Forests (MP, TW), pp. 498–501.
ICPR-v2-2006-SundaresanC #modelling #segmentation: Segmentation and Probabilistic Registration of Articulated Body Models (AS, RC), pp. 92–96.
ICPR-v2-2006-WangH #equation #using: Probabilistic Relaxation using the Heat Equation (HW, ERH), pp. 666–669.
ICPR-v3-2006-El-BazFGEE #image #modelling: Probabilistic Modeling of Blood Vessels for Segmenting MRA Images (AEB, AAF, GLG, MAEG, TE), pp. 917–920.
ICPR-v3-2006-LiC #classification #nearest neighbour #using: Classification Using the Local Probabilistic Centers of k-Nearest Neighbors (BYL, YWC), pp. 1220–1223.
ICPR-v3-2006-PlotzFHKLMMSSS #automation #detection #modelling #music #using: Automatic Detection of Song Changes in Music Mixes Using Stochastic Models (TP, GAF, PH, SK, KL, TM, MM, LS, MS, HS), pp. 665–668.
ICPR-v3-2006-QingSCG #recognition: Face Recognition under Varying Lighting Based on the Probabilistic Model of Gabor Phase (LQ, SS, XC, WG), pp. 1139–1142.
ICPR-v3-2006-TranP #pervasive #process #representation: A probabilistic model with parsinomious representation for sensor fusion in recognizing activity in pervasive environment (DTT, DQP), pp. 168–172.
ICPR-v3-2006-TuIXFH #invariant #recognition: Variational Shift Invariant Probabilistic PCA for Face Recognition (JT, AI, XX, FFL, TSH), pp. 548–551.
ICPR-v3-2006-WangWKH #using #video: Tracking a Variable Number of Human Groups in Video Using Probability Hypothesis Density (YDW, JKW, AAK, WH), pp. 1127–1130.
ICPR-v3-2006-WillamowskiC #automation #detection: Probabilistic Automatic Red Eye Detection and Correction (JW, GC), pp. 762–765.
ICPR-v3-2006-YeungS #framework #set #symmetry: Stochastic Framework for Symmetric Affine Matching between Point Sets (SKY, PS), pp. 790–793.
ICPR-v3-2006-ZhuDJ #modelling: Compound Stochastic Models For Fingerprint Individuality (YZ, SCD, AKJ), pp. 532–535.
ICPR-v4-2006-LiC06a #classification #nearest neighbour #using: Classification Using the Local Probabilistic Centers of k-Nearest Neighbors (BYL, YWC), p. 954.
ICPR-v4-2006-WangS06c #multi #performance #visual notation: Efficient Visual Tracking by Probabilistic Fusion of Multiple Cues (HW, DS), pp. 892–895.
KDD-2006-HashimotoAUKM #mining #order #performance: A new efficient probabilistic model for mining labeled ordered trees (KH, KFAK, NU, MK, HM), pp. 177–186.
KDD-2006-WangP #modelling #using: Summarizing itemset patterns using probabilistic models (CW, SP), pp. 730–735.
KDD-2006-YuYTKW #analysis #component: Supervised probabilistic principal component analysis (SY, KY, VT, HPK, MW), pp. 464–473.
KR-2006-DuboisGK #abduction: Probabilistic Abduction without Priors (DD, AG, GKI), pp. 420–430.
SEKE-2006-HuangC #rule-based #similarity #using: Using Conditional Probability to Measure Rule-based Knowledge Similarity (CJH, MYC), pp. 41–44.
SIGIR-2006-ChenK #documentation #less is more #modelling: Less is more: probabilistic models for retrieving fewer relevant documents (HC, DRK), pp. 429–436.
SIGIR-2006-HanSR: Probabilistic model for definitional question answering (KSH, YIS, HCR), pp. 212–219.
SIGIR-2006-LillisTCD #approach #data fusion #named: ProbFuse: a probabilistic approach to data fusion (DL, FT, RWC, JD), pp. 139–146.
SIGIR-2006-RollekeW #information retrieval #modelling #parallel: A parallel derivation of probabilistic information retrieval models (TR, JW), pp. 107–114.
SIGIR-2006-YanH #analysis #multi #query #retrieval: Probabilistic latent query analysis for combining multiple retrieval sources (RY, AGH), pp. 324–331.
QAPL-2005-AghaMS06 #named #object-oriented #specification: PMaude: Rewrite-based Specification Language for Probabilistic Object Systems (GAA, JM, KS), pp. 213–239.
QAPL-2005-BaierDG06 #branch #partial order #reduction: Partial Order Reduction for Probabilistic Branching Time (CB, PRD, MG), pp. 97–116.
QAPL-2005-KwiatkowskaNP06 #analysis #model checking: Quantitative Analysis With the Probabilistic Model Checker PRISM (MZK, GN, DP), pp. 5–31.
QAPL-2005-LanotteMT06 #classification #security: A Classification of Time and/or Probability Dependent Security Properties (RL, AMS, AT), pp. 177–193.
QAPL-2005-McIverM06 #calculus #game studies #novel #μ-calculus: A Novel Stochastic Game Via the Quantitative μ-calculus (AM, CM), pp. 195–212.
PADL-2006-ErwigK #evolution #modelling #programming: Modeling Genome Evolution with a DSEL for Probabilistic Programming (ME, SK), pp. 134–149.
PLDI-2006-BergerZ #memory management #named #safety: DieHard: probabilistic memory safety for unsafe languages (EDB, BGZ), pp. 158–168.
QAPL-2006-Bortolussi #concurrent #constraints #programming: Stochastic Concurrent Constraint Programming (LB), pp. 65–80.
QAPL-2006-PradalierP: Expressiveness of Probabilistic pi (SP, CP), pp. 119–136.
QAPL-2006-VigliottiH #calculus: Stochastic Ambient Calculus (MGV, PGH), pp. 169–186.
QAPL-2006-WolfBM06a #nondeterminism #semantics: Trace Semantics for Stochastic Systems with Nondeterminism (VW, CB, MEMC), pp. 187–204.
SAC-2006-AltLM #linear #on the #problem #using: On the numerical solution to linear problems using stochastic arithmetic (RA, JLL, SM), pp. 1635–1639.
SAC-2006-DextersPG #algorithm #analysis: A probability analysis for candidate-based frequent itemset algorithms (ND, PWP, DVG), pp. 541–545.
SAC-2006-Lecca #algorithm #π-calculus: A time-dependent extension of gillespie algorithm for biochemical stochastic π-calculus (PL), pp. 137–144.
SAC-2006-SemghouniSAB #realtime #transaction: Stochastic study of real-time transactions success ratio (SS, BS, LA, AB), pp. 513–514.
ASPLOS-2006-SilvaS #analysis #optimisation #pointer: A probabilistic pointer analysis for speculative optimizations (JDS, JGS), pp. 416–425.
CASE-2006-HuSHL #modelling #using: Vision-based Indoor Scene Cognition Using a Spatial Probabilistic Modeling Method (JSH, TMS, HCH, PCL), pp. 620–625.
CASE-2006-LiZY #development #fault #integration #research: Research on Computational Method of Fault Probability for New Product Development Based on Intelligence and Integration (FL, LZ, YY), pp. 319–324.
DAC-2006-GhantaVBP #analysis #correlation #power management #scalability: Stochastic variational analysis of large power grids considering intra-die correlations (PG, SBKV, SB, RP), pp. 211–216.
DAC-2006-SingheeFMR #statistics #tool support #towards: Probabilistic interval-valued computation: toward a practical surrogate for statistics inside CAD tools (AS, CFF, JDM, RAR), pp. 167–172.
DAC-2006-WangKO #nondeterminism #parametricity #statistics: Statistical timing based on incomplete probabilistic descriptions of parameter uncertainty (WSW, VK, MO), pp. 161–166.
DATE-2006-ChakrapaniACKPS #architecture #embedded: Ultra-efficient (embedded) SOC architectures based on probabilistic CMOS (PCMOS) technology (LNC, BESA, SC, PK, KVP, BS), pp. 1110–1115.
DATE-2006-HassenT #on the #term rewriting #verification: On the numerical verification of probabilistic rewriting systems (JBH, ST), pp. 1223–1224.
DATE-2006-WangCG #fault #formal method #testing #using: Test set enrichment using a probabilistic fault model and the theory of output deviations (ZW, KC, MG), pp. 1270–1275.
HPCA-2006-RileyZ #predict: Probabilistic counter updates for predictor hysteresis and stratification (NR, CBZ), pp. 110–120.
HPDC-2006-ZhengYS #algorithm #grid #how #novel #scheduling: How to avoid herd: a novel stochastic algorithm in grid scheduling (QZ, HY, YS), pp. 267–278.
PDP-2006-GlatardMP #clustering #framework #grid #optimisation: Probabilistic and Dynamic Optimization of Job Partitioning on a Grid Infrastructure (TG, JM, XP), pp. 231–238.
STOC-2006-FleischerKLS #multi: Simple cost sharing schemes for multicommodity rent-or-buy and stochastic Steiner tree (LF, JK, SL, GS), pp. 663–670.
STOC-2006-LeviRS #algorithm #modelling: Provably near-optimal sampling-based algorithms for Stochastic inventory control models (RL, RR, DBS), pp. 739–748.
TACAS-2006-HintonKNP #automation #named #verification: PRISM: A Tool for Automatic Verification of Probabilistic Systems (AH, MZK, GN, DP), pp. 441–444.
CAV-2006-KwiatkowskaNP #model checking #reduction #symmetry: Symmetry Reduction for Probabilistic Model Checking (MZK, GN, DP), pp. 234–248.
CSL-2006-ChadhaMS #reasoning #source code: Reasoning About States of Probabilistic Sequential Programs (RC, PM, AS), pp. 240–255.
ISSTA-2006-SevcikovaBSB #approach #automation #statistics #testing: Automated testing of stochastic systems: a statistically grounded approach (HS, AB, DS, WGB), pp. 215–224.
LICS-2006-BrazdilBFK #game studies: Stochastic Games with Branching-Time Winning Objectives (TB, VB, VF, AK), pp. 349–358.
LICS-2006-Kozen #induction #process #proving: Coinductive Proof Principles for Stochastic Processes (DK), pp. 359–366.
TestCom-2006-DiazNR #testing: Customized Testing for Probabilistic Systems (LFLD, MN, IR), pp. 87–102.
VMCAI-2006-Younes #fault #model checking: Error Control for Probabilistic Model Checking (HLSY), pp. 142–156.
ICDAR-2005-HandleyNZ #comprehension #context-free grammar #documentation #using: Document Understanding System Using Stochastic Context-Free Grammars (JCH, AMN, RZ), pp. 511–515.
SIGMOD-2005-JermaineDAJP: A Disk-Based Join With Probabilistic Guarantees (CJ, AD, SA, SJ, AP), pp. 563–574.
SIGMOD-2005-SuciuD #query: Foundations of probabilistic answers to queries (DS, NND), p. 963.
SIGMOD-2005-XieYC #on the: On Joining and Caching Stochastic Streams (JX, JY, YC), pp. 359–370.
VLDB-2005-DalviS #query #statistics: Answering Queries from Statistics and Probabilistic Views (NND, DS), pp. 805–816.
VLDB-2005-TaoCXNKP #multi #nondeterminism: Indexing Multi-Dimensional Uncertain Data with Arbitrary Probability Density Functions (YT, RC, XX, WKN, BK, SP), pp. 922–933.
CIAA-2005-HigueraPT #automaton #finite #learning #recognition: Learning Stochastic Finite Automata for Musical Style Recognition (CdlH, FP, FT), pp. 345–346.
ICALP-2005-ChatterjeeAH #complexity #game studies: The Complexity of Stochastic Rabin and Streett Games (KC, LdA, TAH), pp. 878–890.
ICALP-2005-DattaDMST #logic #polynomial #protocol #security #semantics: Probabilistic Polynomial-Time Semantics for a Protocol Security Logic (AD, AD, JCM, VS, MT), pp. 16–29.
ICALP-2005-EtessamiY #game studies #markov #process #recursion: Recursive Markov Decision Processes and Recursive Stochastic Games (KE, MY), pp. 891–903.
ICALP-2005-GuptaP: Stochastic Steiner Trees Without a Root (AG, MP), pp. 1051–1063.
FM-2005-CelikuM #composition #cost analysis #source code #specification: Compositional Specification and Analysis of Cost-Based Properties in Probabilistic Programs (OC, AM), pp. 107–122.
AIIDE-2005-Darken #towards: Towards Learned Anticipation in Complex Stochastic Environments (CD), pp. 27–32.
CIG-2005-PapacostantisEF #algorithm #game studies #optimisation #using: Coevolving Probabilistic Game Playing Agents using Particle Swarm Optimization Algorithm (EP, APE, NF).
EDOC-2005-PoernomoJS #constraints #distributed: Timed Probabilistic Constraints over the Distributed Management Taskforce Common Information Model (IP, JJ, HWS), pp. 261–272.
CIKM-2005-NottelmannS #information retrieval #machine learning: Information retrieval and machine learning for probabilistic schema matching (HN, US), pp. 295–296.
ECIR-2005-GoutteG #evaluation #precise: A Probabilistic Interpretation of Precision, Recall and F-Score, with Implication for Evaluation (CG, ÉG), pp. 345–359.
ECIR-2005-Nottelmann #datalog #information retrieval #named: PIRE: An Extensible IR Engine Based on Probabilistic Datalog (HN), pp. 260–274.
ECIR-2005-NottelmannS #approach #named: sPLMap: A Probabilistic Approach to Schema Matching (HN, US), pp. 81–95.
ECIR-2005-Rijsbergen #information retrieval #logic: A Probabilistic Logic for Information Retrieval (CJvR), pp. 1–6.
ICML-2005-CalinonB #framework #gesture #recognition #using: Recognition and reproduction of gestures using a probabilistic framework combining PCA, ICA and HMM (SC, AB), pp. 105–112.
ICML-2005-CarneyCDL #network #predict #using: Predicting probability distributions for surf height using an ensemble of mixture density networks (MC, PC, JD, CL), pp. 113–120.
ICML-2005-JinZ #algorithm #using: A smoothed boosting algorithm using probabilistic output codes (RJ, JZ), pp. 361–368.
ICML-2005-LowdD #estimation #modelling #naive bayes: Naive Bayes models for probability estimation (DL, PMD), pp. 529–536.
ICML-2005-NatarajanTADFR #first-order #learning #modelling: Learning first-order probabilistic models with combining rules (SN, PT, EA, TGD, AF, ACR), pp. 609–616.
KDD-2005-LangeB: Combining partitions by probabilistic label aggregation (TL, JMB), pp. 147–156.
KDD-2005-SilvaZS #mining #workflow: Probabilistic workflow mining (RBdAeS, JZ, JGS), pp. 275–284.
MLDM-2005-NikulinS #clustering: Universal Clustering with Regularization in Probabilistic Space (VN, AJS), pp. 142–152.
SIGIR-2005-AzzopardiGC: Probabilistic hyperspace analogue to language (LA, MG, MC), pp. 575–576.
SIGIR-2005-LiWLM #detection: A probabilistic model for retrospective news event detection (ZL, BW, ML, WYM), pp. 106–113.
SIGIR-2005-WuLWKL #retrieval: A retrospective study of probabilistic context-based retrieval (HCW, RWPL, KFW, KLK, WJL), pp. 663–664.
ECMDA-FA-2005-TabuchiSN #algebra #analysis #design #modelling #performance #process #uml: Model-Driven Performance Analysis of UML Design Models Based on Stochastic Process Algebra (NT, NS, HN), pp. 41–58.
QAPL-2004-AldiniP05 #analysis #on the #protocol: On Quantitative Analysis of Probabilistic Protocols (AA, ADP), pp. 131–148.
QAPL-2004-HurdMM05: Probabilistic Guarded Commands Mechanized in HOL (JH, AM, CM), pp. 95–111.
PADL-2005-SaadP #framework #hybrid #logic programming #towards: Towards a More Practical Hybrid Probabilistic Logic Programming Framework (ES, EP), pp. 67–82.
POPL-2005-ParkPT: A probabilistic language based upon sampling functions (SP, FP, ST), pp. 171–182.
RE-2005-RobinsonWW #analysis #design #requirements #using: Risk Mitigation of Design Requirements Using a Probabilistic Analysis (MCR, SEW, DCW), pp. 231–239.
SAC-2005-BarrettEKMS #ad hoc #multi #network #protocol: Probabilistic multi-path vs. deterministic single-path protocols for dynamic ad-hoc network scenarios (CLB, SE, LK, MVM, JPS), pp. 1166–1173.
SAC-2005-DiazLPCV #approach #behaviour #e-commerce #protocol #realtime #set #validation: An approach to handle real time and probabilistic behaviors in e-commerce: validating the SET protocol (GD, KGL, JJP, FC, VV), pp. 815–820.
SAC-2005-PandeyGM #algorithm #learning #scheduling: Stochastic scheduling of active support vector learning algorithms (GP, HG, PM), pp. 38–42.
CASE-2005-TanonkouBBX #approach #problem #using: Solving a stochastic inventory-location problem using Lagrangian relaxation approach (GAT, LB, RB, XX), pp. 279–284.
DAC-2005-NepalBMPZ #design #logic: Designing logic circuits for probabilistic computation in the presence of noise (KN, RIB, JLM, WRP, AZ), pp. 485–490.
DATE-2005-AsadiT #estimation: An Accurate SER Estimation Method Based on Propagation Probability (GA, MBT), pp. 306–307.
DATE-2005-GhantaVPW #analysis #grid #power management #process: Stochastic Power Grid Analysis Considering Process Variations (PG, SBKV, RP, JMW), pp. 964–969.
DATE-2005-KrishnaswamyVMH #evaluation #matrix #reliability: Accurate Reliability Evaluation and Enhancement via Probabilistic Transfer Matrices (SK, GFV, ILM, JPH), pp. 282–287.
DATE-2005-KumarLTW #multi #process #statistics: A Probabilistic Collocation Method Based Statistical Gate Delay Model Considering Process Variations and Multiple Input Switching (YSK, JL, CT, JMW), pp. 770–775.
LCTES-2005-FrankeOTF #embedded #optimisation #source code: Probabilistic source-level optimisation of embedded programs (BF, MFPO, JT, GF), pp. 78–86.
FoSSaCS-2005-AbbesB #branch: Branching Cells as Local States for Event Structures and Nets: Probabilistic Applications (SA, AB), pp. 95–109.
FoSSaCS-2005-CattaniSKN #nondeterminism: Stochastic Transition Systems for Continuous State Spaces and Non-determinism (SC, RS, MZK, GN), pp. 125–139.
FoSSaCS-2005-DengP #axiom #behaviour #finite: Axiomatizations for Probabilistic Finite-State Behaviors (YD, CP), pp. 110–124.
FoSSaCS-2005-LanotteT #congruence #generative #process: Probabilistic Congruence for Semistochastic Generative Processes (RL, ST), pp. 63–78.
FoSSaCS-2005-LaroussinieS #model checking: Model Checking Durational Probabilistic Systems (FL, JS), pp. 140–154.
STOC-2005-AdlerEM #towards: Towards asymptotic optimality in probabilistic packet marking (MA, JE, JM), pp. 450–459.
TACAS-2005-EtessamiY #algorithm #recursion #state machine #verification: Algorithmic Verification of Recursive Probabilistic State Machines (KE, MY), pp. 253–270.
CAV-2005-0002G #modelling #protocol #verification: Improved Probabilistic Models for 802.11 Protocol Verification (AR, KG), pp. 239–252.
CAV-2005-SenVA #model checking #on the #statistics: On Statistical Model Checking of Stochastic Systems (KS, MV, GA), pp. 266–280.
CAV-2005-Younes #black box #verification: Probabilistic Verification for “Black-Box” Systems (HLSY), pp. 253–265.
ICLP-2005-BortolussiW #concurrent #constraints #distributed #programming language: A Distributed and Probabilistic Concurrent Constraint Programming Language (LB, HW), pp. 143–158.
ICLP-2005-SaadP #hybrid #logic programming #source code: Hybrid Probabilistic Logic Programs with Non-monotonic Negation (ES, EP), pp. 204–220.
LICS-2005-BaierG #automaton #regular expression: Recognizing ω-regular Languages with Probabilistic Automata (CB, MG), pp. 137–146.
LICS-2005-EsparzaKM #analysis #automaton: Quantitative Analysis of Probabilistic Pushdown Automata: Expectations and Variances (JE, AK, RM), pp. 117–126.
TestCom-2005-LiL05a #algorithm #detection #fault #network #testing: Fault Detection of Hierarchical Networks with Probabilistic Testing Algorithms (KL, DL), pp. 258–274.
VLDB-2004-ChaudhuriDHW #database #query #ranking: Probabilistic Ranking of Database Query Results (SC, GD, VH, GW), pp. 888–899.
VLDB-2004-ChengXPSV #nondeterminism #performance #query: Efficient Indexing Methods for Probabilistic Threshold Queries over Uncertain Data (RC, YX, SP, RS, JSV), pp. 876–887.
VLDB-2004-DalviS #database #evaluation #performance #query: Efficient Query Evaluation on Probabilistic Databases (NND, DS), pp. 864–875.
VLDB-2004-TheobaldWS #evaluation #query: Top-k Query Evaluation with Probabilistic Guarantees (MT, GW, RS), pp. 648–659.
VLDB-2004-ZhuR #consistency #data flow #scalability: Stochastic Consistency, and Scalable Pull-Based Caching for Erratic Data Sources (SZ, CVR), pp. 192–203.
CIAA-2004-Shan #graph grammar #modelling: Stochastic Context-Free Graph Grammars for Glycoprotein Modelling (BS), pp. 247–258.
SEFM-2004-BertoliniFFO #analysis #automaton #generative #network #testing #using: Test Case Generation Using Stochastic Automata Networks: Quantitative Analysis (CB, AGF, PF, FMO), pp. 251–260.
SEFM-2004-LanotteMT #decidability #parametricity #security: Decidability Results for Parametric Probabilistic Transition Systems with an Application to Security (RL, AMS, AT), pp. 114–121.
SFM-2004-Bravetti #realtime: Real Time and Stochastic Time (MB), pp. 132–180.
ICGT-2004-HeckelLM #graph transformation: Stochastic Graph Transformation Systems (RH, GL, SM), pp. 210–225.
ICEIS-v2-2004-Martinez-OtzetaS #algorithm #analysis #nearest neighbour: Analysis of the Iterated Probabilistic Weighted K Nearest Neighbor Method, a new Distance-Based Algorithm (JMMO, BS), pp. 233–240.
ICEIS-v2-2004-WuW #predict #using #web: Predicting Web Requests Efficiently Using a Probability Model (SW, WW), pp. 48–53.
ICML-2004-EliazarP #learning #mobile #modelling: Learning probabilistic motion models for mobile robots (AIE, RP).
ICML-2004-LeeWZB #perspective: Probabilistic tangent subspace: a unified view (JL, JW, CZ, ZB).
ICML-2004-SuD #automation #component: Automated hierarchical mixtures of probabilistic principal component analyzers (TS, JGD).
ICML-2004-SuttonRM #modelling #random #sequence: Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data (CAS, KR, AM).
ICML-2004-Zhang #algorithm #linear #predict #problem #scalability #using: Solving large scale linear prediction problems using stochastic gradient descent algorithms (TZ0).
ICML-2004-ZhangY #estimation: Probabilistic score estimation with piecewise logistic regression (JZ, YY).
ICPR-v1-2004-CucchiaraGTV #people: Probabilistic People Tracking for Occlusion Handling (RC, CG, GT, RV), pp. 132–135.
ICPR-v1-2004-LoogG #detection: Static Posterior Probability Fusion for Signal Detection: Applications in the Detection of Interstitial Diseases in Chest Radiographs (ML, BvG), pp. 644–647.
ICPR-v1-2004-MaedaKI #clustering #data-driven #database #process #segmentation: Segmentation of Range Data Based on A Stochastic Clustering Method with Competitive Process (MM, KK, KI), pp. 624–627.
ICPR-v1-2004-ThirdeJ #modelling #segmentation #video: Hierarchical Probabilistic Models for Video Object Segmentation and Tracking (DT, GAJ), pp. 636–639.
ICPR-v1-2004-VaswaniC #analysis #classification #component #null: Classification Probability Analysis of Principal Component Null Space Analysis (NV, RC), pp. 240–243.
ICPR-v1-2004-WithagenSG #classification: Probabilistic Classification Between Foreground Objects and Background (PJW, KS, FCAG), pp. 31–34.
ICPR-v2-2004-AltmuellerH #approximate: Approximating High Dimensional Probability Distributions (SA, RMH), pp. 299–302.
ICPR-v2-2004-ChenLF #adaptation #feature model: Probabilistic Tracking with Adaptive Feature Selection (HTC, TLL, CSF), pp. 736–739.
ICPR-v2-2004-GimelfarbGZ #modelling #question: To FRAME or not to FRAME in Probabilistic Texture Modelling? (GLG, LJVG, AZ), pp. 707–711.
ICPR-v2-2004-HuR #classification #clustering #using: Probability Table Compression Using Distributional Clustering for Scanning N-Tuple Classifiers (JH, ER), pp. 533–536.
ICPR-v2-2004-IurgelR #classification #documentation #using: Spoken Document Classification with SVMs Using Linguistic Unit Weighting and Probabilistic Couplers (UI, GR), pp. 667–670.
ICPR-v2-2004-OdobezG #modelling: Embedding Motion in Model-Based Stochastic Tracking (JMO, DGP), pp. 815–818.
ICPR-v2-2004-SerbyKG #multi #using: Probabilistic Object Tracking Using Multiple Features (DS, EKM, LJVG), pp. 184–187.
ICPR-v2-2004-TanakaT #image: Probabilistic Image Processing based on the Q-Ising Model by Means of the Mean-Field Method and Loopy Belief Propagation (KT, DMT), pp. 40–43.
ICPR-v2-2004-ValasoulisL #image #retrieval: Probabilistic Shape-Based Image Indexing and Retrieval (KV, AL), pp. 969–972.
ICPR-v2-2004-VillegerAB #image #using: Image Disocclusion Using a Probabilistic Gradient Orientation (EV, GA, LBF), pp. 52–55.
ICPR-v2-2004-WillisSC #3d: Surface Sculpting with Stochastic Deformable 3D Surfaces (ARW, JS, DBC), pp. 249–252.
ICPR-v3-2004-FangD #estimation #pattern matching #pattern recognition #recognition: Improvement of ICA Based Probability Density Estimation for Pattern Recognition (CF, XD), pp. 466–469.
ICPR-v3-2004-GrossK #mobile #robust #scalability #self: Robust Omniview-based Probabilistic Self-Localization for Mobile Robots in Large Maze-like Environments (HMG, AK), pp. 266–269.
ICPR-v3-2004-KapoorPI #detection #multi: Probabilistic Combination of Multiple Modalities to Detect Interest (AK, RWP, YI), pp. 969–972.
ICPR-v3-2004-NeuhausB #approach #distance #edit distance #graph #learning: A Probabilistic Approach to Learning Costs for Graph Edit Distance (MN, HB), pp. 389–393.
ICPR-v4-2004-BaO #estimation #framework: A Probabilistic Framework for Joint Head Tracking and Pose Estimation (SOB, JMO), pp. 264–267.
ICPR-v4-2004-ImbaultL #approach #optimisation #parametricity: A Stochastic Optimization Approach for Parameter Tuning of Support Vector Machines (FI, KL), pp. 597–600.
ICPR-v4-2004-PeternelL #learning #recognition #visual notation: Visual Learning and Recognition of a Probabilistic Spatio-Temporal Model of Cyclic Human Locomotion (MP, AL), pp. 146–149.
ICPR-v4-2004-PiriouBY #detection #image #modelling: Learned Probabilistic Image Motion Models for Event Detection in Videos (GP, PB, JFY), pp. 207–210.
ICPR-v4-2004-TanakaOKK #locality #mobile #using: Probabilistic Localization for Mobile Robots using Incomplete Maps (KT, NO, EK, YK), pp. 709–712.
ICPR-v4-2004-UlusoyHH: Probabilistic Phase Based Sparse Stereo (IU, UH, ERH), pp. 84–87.
KDD-2004-BasuBM #clustering #framework: A probabilistic framework for semi-supervised clustering (SB, MB, RJM), pp. 59–68.
KDD-2004-JinZM #analysis #mining #semantics #web: Web usage mining based on probabilistic latent semantic analysis (XJ, YZ, BM), pp. 197–205.
KDD-2004-SteyversSRG #modelling #topic: Probabilistic author-topic models for information discovery (MS, PS, MRZ, TLG), pp. 306–315.
KDD-2004-TinoKS #approach #generative #sequence #set #visualisation: A generative probabilistic approach to visualizing sets of symbolic sequences (PT, AK, YS), pp. 701–706.
KR-2004-Lukasiewicz #logic: Weak Nonmonotonic Probabilistic Logics (TL), pp. 23–33.
KR-2004-PasulaZK #learning #relational: Learning Probabilistic Relational Planning Rules (HP, LSZ, LPK), pp. 683–691.
KR-2004-SmythP: Qualitative Probabilistic Matching with Hierarchical Descriptions (CS, DP), pp. 479–487.
SIGIR-2004-Ogilvie #comprehension #generative #information retrieval #modelling #using: Understanding combination of evidence using generative probabilistic models for information retrieval (PO), p. 603.
SIGIR-2004-WenLM #retrieval: Probabilistic model for contextual retrieval (JRW, NL, WYM), pp. 57–63.
SAC-2004-LeccaPLC #predict #π-calculus: Predicting cell adhesion probability via the biochemical stochastic π-calculus (PL, CP, CL, GC), pp. 211–212.
CC-2004-OzerNG #approximate #using: Stochastic Bit-Width Approximation Using Extreme Value Theory for Customizable Processors (EÖ, AN, DG), pp. 250–264.
CGO-2004-SmelyanskiyMD #scheduling: Probabilistic Predicate-Aware Modulo Scheduling (MS, SAM, ESD), pp. 151–162.
DAC-2004-FineUZ #functional #verification: Probabilistic regression suites for functional verification (SF, SU, AZ), pp. 49–54.
DAC-2004-JacomeHVB #design #fault #paradigm: Defect tolerant probabilistic design paradigm for nanotechnologies (MFJ, CH, GdV, SB), pp. 596–601.
DAC-2004-PantBZSP #analysis #approach #grid #power management: A stochastic approach To power grid analysis (SP, DB, VZ, SS, RP), pp. 171–176.
DATE-v1-2004-FernandesSOT #testing: A Probabilistic Method for the Computation of Testability of RTL Constructs (JMF, MBS, ALO, JPT), pp. 176–181.
DATE-v2-2004-HuangCHTHH #analysis #fault: Intermittent Scan Chain Fault Diagnosis Based on Signal Probability Analysis (YH, WTC, CJH, HYT, AH, YTH), pp. 1072–1077.
DATE-v2-2004-OlbrichB #locality #using: Placement Using a Localization Probability Model (LPM) (MO, EB), p. 1412.
FoSSaCS-2004-RamanathanMST #analysis #bisimulation #equivalence #network #protocol #security: Probabilistic Bisimulation and Equivalence for Security Analysis of Network Protocols (AR, JCM, AS, VT), pp. 468–483.
FoSSaCS-2004-Zielonka #game studies: Perfect-Information Stochastic Parity Games (WZ), pp. 499–513.
STOC-2004-GuptaPRS #algorithm #approximate #optimisation: Boosted sampling: approximation algorithms for stochastic optimization (AG, MP, RR, AS), pp. 417–426.
TACAS-2004-YounesKNP #empirical #model checking #statistics: Numerical vs. Statistical Probabilistic Model Checking: An Empirical Study (HLSY, MZK, GN, DP), pp. 46–60.
CAV-2004-SenVA #black box #model checking #statistics: Statistical Model Checking of Black-Box Probabilistic Systems (KS, MV, GA), pp. 202–215.
CSL-2004-ChatterjeeMJ #game studies #nash #on the: On Nash Equilibria in Stochastic Games (KC, RM, MJ), pp. 26–40.
ICLP-2004-DekhtyarD #logic programming #semantics #source code: Possible Worlds Semantics for Probabilistic Logic Programs (AD, MID), pp. 137–148.
ICLP-2004-PetitG #constraints #statistics #testing: Probabilistic Choice Operators as Global Constraints: Application to Statistical Software Testing (MP, AG), pp. 471–472.
LICS-2004-EsparzaKM #automaton #model checking: Model Checking Probabilistic Pushdown Automata (JE, AK, RM), pp. 12–21.
VMCAI-2004-HeraultLMP #approximate #model checking: Approximate Probabilistic Model Checking (TH, RL, FM, SP), pp. 73–84.
DRR-2003-JinZH #documentation #information retrieval: Information retrieval for OCR documents: a content-based probabilistic correction model (RJ, CZ, AGH), pp. 128–135.
ECDL-2003-NottelmannF #logic #nondeterminism: Combining DAML+OIL, XSLT, and Probabilistic Logics for Uncertain Schema Mappings in MIND (HN, NF), pp. 194–206.
ICDAR-2003-ChoPR #recognition: Probability Table Compression for Handwritten Character Recognition (SJC, MPP, EHR), p. 173–?.
ICDAR-2003-KangK #recognition #representation: Handwritten Hangul Character Recognition with Hierarchical Stochastic Character Representation (KWK, JHK), p. 212–?.
SIGMOD-2003-ChengKP #query: Evaluating Probabilistic Queries over Imprecise Data (RC, DVK, SP), pp. 551–562.
CIAA-2003-DaleyEM #automaton #retrieval: Bag Automata and Stochastic Retrieval of Biomolecules in Solution (MD, MGE, IM), pp. 239–250.
DLT-2003-FalcoGL #modelling: Frequency of Symbol Occurrences in Simple Non-primitive Stochastic Models (DdF, MG, VL), pp. 242–253.
ICALP-2003-DenisE #automaton: Residual Languages and Probabilistic Automata (FD, YE), pp. 452–463.
ICALP-2003-Doberkat #bisimulation #category theory: Semi-pullbacks and Bisimulations in Categories of Stochastic Relations (EED), pp. 996–1007.
ICALP-2003-Rabinovich #analysis: Quantitative Analysis of Probabilistic Lossy Channel Systems (AMR), pp. 1008–1021.
ICALP-2003-StoelingaV #automaton #testing: A Testing Scenario for Probabilistic Automata (MS, FWV), pp. 464–477.
SEFM-2003-LanotteMT #automaton #bisimulation #security: Weak Bisimulation for Probabilistic Timed Automata and Applications to Security (RL, AMS, AT), pp. 34–43.
ICEIS-v2-2003-CamposGM #abduction #network #using: Partial Abductive Inference in Bayesian Networks By Using Probability Trees (LMdC, JAG, SM), pp. 83–91.
ECIR-2003-NottelmannF #information retrieval #nondeterminism: From Uncertain Inference to Probability of Relevance for Advanced IR Applications (HN, NF), pp. 235–250.
ICML-2003-Jaeger #classification #concept: Probabilistic Classifiers and the Concepts They Recognize (MJ), pp. 266–273.
ICML-2003-LachicheF #classification #multi #using: Improving Accuracy and Cost of Two-class and Multi-class Probabilistic Classifiers Using ROC Curves (NL, PAF), pp. 416–423.
ICML-2003-LiWL #classification #generative #keyword #using: Text Classification Using Stochastic Keyword Generation (CL, JRW, HL), pp. 464–471.
ICML-2003-RuckertK #learning: Stochastic Local Search in k-Term DNF Learning (UR, SK), pp. 648–655.
KDD-2003-ChiuKL: Probabilistic discovery of time series motifs (BYcC, EJK, SL), pp. 493–498.
KDD-2003-NevilleJFH #learning #relational: Learning relational probability trees (JN, DJ, LF, MH), pp. 625–630.
KDD-2003-SarawagiCG #learning #named #topic: Cross-training: learning probabilistic mappings between topics (SS, SC, SG), pp. 177–186.
MLDM-2003-LazliS #fuzzy #logic #recognition #speech #using: Connectionist Probability Estimators in HMM Arabic Speech Recognition Using Fuzzy Logic (LL, MS), pp. 379–388.
SIGIR-2003-Bennett #classification #symmetry #using: Using asymmetric distributions to improve text classifier probability estimates (PNB), pp. 111–118.
SIGIR-2003-BruzaS #comparison #dependence #modelling #using: A comparison of various approaches for using probabilistic dependencies in language modeling (PB, DS), pp. 419–420.
SIGIR-2003-DarwishO #query: Probabilistic structured query methods (KD, DWO), pp. 338–344.
SIGIR-2003-Hofmann #analysis #collaboration #semantics: Collaborative filtering via gaussian probabilistic latent semantic analysis (TH), pp. 259–266.
SIGIR-2003-Roelleke: A frequency-based and a poisson-based definition of the probability of being informative (TR), pp. 227–234.
SIGIR-2003-TeevanK #analysis #development #empirical #exponential #retrieval #using: Empirical development of an exponential probabilistic model for text retrieval: using textual analysis to build a better model (JT, DRK), pp. 18–25.
SIGIR-2003-TsuruokaT #generative: Probabilistic term variant generator for biomedical terms (YT, JT), pp. 167–173.
SIGIR-2003-WesterveldV #analysis #generative #image #retrieval: Experimental result analysis for a generative probabilistic image retrieval model (TW, APdV), pp. 135–142.
DATE-2003-DumitrasM #communication: On-Chip Stochastic Communication (TD, RM), pp. 10790–10795.
PPoPP-2003-ChenHHJL #analysis #architecture #compilation #multi #points-to #thread: Compiler support for speculative multithreading architecture with probabilistic points-to analysis (PSC, MYH, YSH, RDCJ, JKL), pp. 25–36.
FoSSaCS-2003-AbdullaR #communication #verification: Verification of Probabilistic Systems with Faulty Communication (PAA, AMR), pp. 39–53.
FoSSaCS-2003-AronsPZ #abstraction #verification: Parameterized Verification by Probabilistic Abstraction (TA, AP, LDZ), pp. 87–102.
FoSSaCS-2003-BreugelMOW #approximate #similarity: An Intrinsic Characterization of Approximate Probabilistic Bisimilarity (FvB, MWM, JO, JW), pp. 200–215.
FoSSaCS-2003-Doberkat: The Converse of a Stochastic Relation (EED), pp. 233–249.
STOC-2003-AdlerHKV #network #peer-to-peer #process: A stochastic process on the hypercube with applications to peer-to-peer networks (MA, EH, RMK, VVV), pp. 575–584.
STOC-2003-Tardo: Optimal probabilistic fingerprint codes (GT), pp. 116–125.
CSL-2003-ChatterjeeJH #game studies: Simple Stochastic Parity Games (KC, MJ, TAH), pp. 100–113.
CSL-2003-MeydenP #logic #quantum: A Logic for Probability in Quantum Systems (RvdM, MP), pp. 427–440.
LICS-2003-Kwiatkowska #model checking #theory and practice: Model checking for probability and time: from theory to practice (MZK), p. 351–?.
SAT-2003-BaumerS #algorithm #independence #satisfiability: Improving a Probabilistic 3-SAT Algorithm by Dynamic Search and Independent Clause Pairs (SB, RS), pp. 150–161.
SAT-2003-Parisi #approach #on the #problem #random #satisfiability: On the Probabilistic Approach to the Random Satisfiability Problem (GP), pp. 203–213.
CBSE-2002-Mason #analysis #component #composition #reliability: Probabilistic Analysis for Component Reliability Composition (DM), p. 8.
VLDB-2002-NiermanJ #named #xml: ProTDB: Probabilistic Data in XML (AN, HVJ), pp. 646–657.
DLT-2002-SasakiIIW #2d #bound #turing machine: A Space Lower Bound of Two-Dimensional Probabilistic Turing Machines (YS, KI, AI, YW), pp. 185–196.
ICALP-2002-AblayevMP #bound #branch #quantum #source code: Quantum and Stochastic Branching Programs of Bounded Width (FMA, CM, CP), pp. 343–354.
ICALP-2002-MartinMW: Measuring the Probabilistic Powerdomain (KM, MWM, JW), pp. 463–475.
ICALP-2002-Merkle #sequence: The Kolmogorov-Loveland Stochastic Sequences Are Not Closed under Selecting Subsequences (WM), pp. 390–400.
IFM-2002-LopezNR #algebra #process: Stochastic Process Algebras Meet Eden (NL, MN, FR), pp. 29–48.
RTA-2002-BournezK: Probabilistic Rewrite Strategies. Applications to ELAN (OB, CK), pp. 252–266.
ICEIS-2002-OuziriV #approach #documentation #logic #modelling: Logic and Probabilistic Based Approach for Document Data Modeling (MO, CV), pp. 1126–1129.
CIKM-2002-BrantsCT #analysis #documentation #segmentation #semantics #topic: Topic-based document segmentation with probabilistic latent semantic analysis (TB, FC, IT), pp. 211–218.
CIKM-2002-GreiffMP #information retrieval: The role of variance in term weighting for probabilistic information retrieval (WRG, WTM, JMP), pp. 252–259.
ICML-2002-DietterichBMS #learning #refinement: Action Refinement in Reinforcement Learning by Probability Smoothing (TGD, DB, RLdM, CS), pp. 107–114.
ICML-2002-LebanonL #modelling #named #permutation #ranking #using: Cranking: Combining Rankings Using Conditional Probability Models on Permutations (GL, JDL), pp. 363–370.
ICML-2002-LeckieR #distributed #learning: Learning to Share Distributed Probabilistic Beliefs (CL, KR), pp. 371–378.
ICML-2002-WangW #modelling #predict: Modeling for Optimal Probability Prediction (YW, IHW), pp. 650–657.
ICPR-v1-2002-ZhouC #algorithm #recognition #robust: A Robust Algorithm for Probabilistic Human Recognition From (SKZ, RC), pp. 226–229.
ICPR-v2-2002-CesarBB #graph #optimisation #recognition #using: Inexact Graph Matching Using Stochastic Optimization Techniques for Facial Feature Recognition (RMC, EB, IB), pp. 465–468.
ICPR-v2-2002-ChenL: Probabilistic Tracking with Optimal Scale and Orientation Selection (HTC, TLL), pp. 668–671.
ICPR-v2-2002-GrimPS #network: Boosting in Probabilistic Neural Networks (JG, PP, PS), pp. 136–139.
ICPR-v2-2002-KirshnerCSKC #detection #modelling: Probabilistic Model-Based Detection of Bent-Double Radio Galaxies (SK, IVC, PS, CK, ECP), pp. 499–502.
ICPR-v2-2002-KovacsS #animation #detection: Creating Animations Combining Stochastic Paintbrush Transformation and Motion Detection (LK, TS), p. 1090–?.
ICPR-v2-2002-SeokL #algorithm #analysis #approach #difference #learning: The Analysis of a Stochastic Differential Approach for Langevine Comepetitive Learning Algorithm (JS, JWL), pp. 80–83.
ICPR-v2-2002-UdeA #detection #using: Probabilistic Detection and Tracking at High Frame Rates Using Affine Warping (AU, CGA), pp. 6–9.
ICPR-v2-2002-WachsmuthS #analysis #image #process #speech: Integrated Analysis of Speech and Images as a Probabilistic Decoding Process (SW, GS), pp. 588–592.
ICPR-v3-2002-AyromlouVP #realtime: Probabilistic Matching of Image- to Model-Features for Real-time Object Tracking (MA, MV, WP), pp. 692–695.
ICPR-v3-2002-GreenspanGG #category theory #generative #image #modelling: Probabilistic Models for Generating, Modelling and Matching Image Categories (HG, SG, JG), pp. 970–973.
ICPR-v3-2002-Horiuchi #estimation #image: Estimation of Color for Gray-level Image by Probabilistic Relaxation (TH), pp. 867–870.
ICPR-v3-2002-JinQH #detection: A Probabilistic Model for Camera Zoom Detection (RJ, YQ, AGH), pp. 859–862.
ICPR-v3-2002-RaghebH #framework: A Probabilistic Framework for Specular Shape-from-Shading (HR, ERH), pp. 513–516.
ICPR-v4-2002-Ichimura #estimation #image #monte carlo #sequence #using: Stochastic Filtering for Motion Trajectory in Image Sequences Using a Monte Carlo Filter with Estimation of Hyper-Parameters (NI), pp. 68–73.
ICPR-v4-2002-KoB02a #feedback #image #multi #network #retrieval: Probabilistic Neural Networks Supporting Multi-Class Relevance Feedback in Region-Based Image Retrieval (BK, HB), pp. 138–141.
KDD-2002-ZadroznyE #classification #multi: Transforming classifier scores into accurate multiclass probability estimates (BZ, CE), pp. 694–699.
KR-2002-MateusPP #calculus: Observations and the Probabilistic Situation Calculus (PM, AP, JP), pp. 327–340.
SEKE-2002-FarinaFO #automaton #modelling #network #representation: Representing software usage models with stochastic automata networks (AGF, PF, FMO), pp. 401–407.
SIGIR-2002-BennettDH #classification #modelling #reliability #using: Probabilistic combination of text classifiers using reliability indicators: models and results (PNB, STD, EH), pp. 207–214.
SIGIR-2002-Westerveld #multi #retrieval: Probabilistic multimedia retrieval (TW), pp. 437–438.
POPL-2002-RamseyP #monad #λ-calculus: Stochastic λ calculus and monads of probability distributions (NR, AP), pp. 154–165.
SAC-2002-Al-SadiDO #algorithm #fault tolerance: Probability vectors: a new fault-tolerant routing algorithm for k-ary n-cubes (JAS, KD, MOK), pp. 830–834.
DAC-2002-OrshanskyK #analysis #framework: A general probabilistic framework for worst case timing analysis (MO, KK), pp. 556–561.
FoSSaCS-2002-Doberkat: The Demonic Product of Probabilistic Relations (EED), pp. 114–128.
STOC-2002-Adler #trade-off: Tradeoffs in probabilistic packet marking for IP traceback (MA), pp. 407–418.
TACAS-2002-KwiatkowskaNP #approach #hybrid #model checking: Probabilistic Symbolic Model Checking with PRISM: A Hybrid Approach (MZK, GN, DP), pp. 52–66.
CAV-2002-YounesS #using #verification: Probabilistic Verification of Discrete Event Systems Using Acceptance Sampling (HLSY, RGS), pp. 223–235.
CSL-2002-BeauquierRS #decidability #logic #model checking: A Logic of Probability with Decidable Model-Checking (DB, AMR, AS), pp. 306–321.
CSL-2002-JurdzinskiKH: Trading Probability for Fairness (MJ, OK, TAH), pp. 292–305.
ICLP-2002-Angelopoulos #finite #overview #perspective: Probabilistic Finite Domains: A Brief Overview (NA), p. 475.
LICS-2002-DesharnaisJGP #bisimulation #metric #process: The Metric Analogue of Weak Bisimulation for Probabilistic Processes (JD, RJ, VG, PP), pp. 413–422.
LICS-2002-LaplanteLMPR #abstraction #approach #model checking #testing: Probabilistic Abstraction for Model Checking: An Approach Based on Property Testing (SL, RL, FM, SP, MdR), pp. 30–39.
SAT-2002-KaporisKL #algorithm #analysis #satisfiability: The Probabilistic Analysis of a Greedy Satisfiability Algorithm (ACK, LMK, EGL), p. 5.
SAT-2002-Pretolani #logic #modelling: Probabilistic logic: The PSAT and CPA models (DP), p. 30.
VMCAI-2002-ZuckPK #automation #verification: Automatic Verification of Probabilistic Free Choice (LDZ, AP, YK), pp. 208–224.
CBSE-2001-Mason #program analysis: Probability Density Functions in Program Analysis (DM), p. 13.
ICDAR-2001-BahlmannB #fault #online #recognition #similarity: Measuring HMM Similarity with the Bayes Probability of Error and its Application to Online Handwriting Recognition (CB, HB), pp. 406–411.
ICDAR-2001-BourgeoisEB #comprehension #documentation #using: Document Understanding Using Probabilistic Relaxation: Application on Tables of Contents of Periodicals (FL, HE, SSB), pp. 508–512.
ICDAR-2001-KimSL #modelling #using: Character Spotting Using Image-Based Stochastic Models (SKK, BKS, SWL), pp. 60–63.
ICDAR-2001-KoshinakaNY #dependence #recognition #using #word: A Stochastic Model for Handwritten Word Recognition Using Context Dependency Between Character Patterns (TK, DN, KY), pp. 154–158.
ICDAR-2001-TulyakovG #recognition #segmentation #word: Probabilistic Model for Segmentation Based Word Recognition with Lexicon (ST, VG), pp. 164–167.
ICALP-2001-BandiniS #axiom #bisimulation: Axiomatizations for Probabilistic Bisimulation (EB, RS), pp. 370–381.
ICALP-2001-BreugelW #towards #verification: Towards Quantitative Verification of Probabilistic Transition Systems (FvB, JW), pp. 421–432.
CIKM-2001-NottelmannF #classification #datalog #learning: Learning Probabilistic Datalog Rules for Information Classification and Transformation (HN, NF), pp. 387–394.
ICML-2001-GetoorFKT #learning #modelling #relational: Learning Probabilistic Models of Relational Structure (LG, NF, DK, BT), pp. 170–177.
ICML-2001-GlickmanS #learning #memory management #policy #search-based: Evolutionary Search, Stochastic Policies with Memory, and Reinforcement Learning with Hidden State (MRG, KPS), pp. 194–201.
ICML-2001-LaffertyMP #modelling #random #sequence: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data (JDL, AM, FCNP), pp. 282–289.
ICML-2001-Thollard #algorithm #grammar inference: Improving Probabilistic Grammatical Inference Core Algorithms with Post-processing Techniques (FT), pp. 561–568.
ICML-2001-ZadroznyE #classification #naive bayes: Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers (BZ, CE), pp. 609–616.
KDD-2001-CadezSM #modelling #predict #profiling #transaction #visualisation: Probabilistic modeling of transaction data with applications to profiling, visualization, and prediction (IVC, PS, HM), pp. 37–46.
KDD-2001-PavlovS #modelling #query #transaction: Probabilistic query models for transaction data (DP, PS), pp. 164–173.
KDD-2001-PennockLNG #game studies #web: Extracting collective probabilistic forecasts from web games (DMP, SL, FÅN, CLG), pp. 174–183.
SIGIR-2001-DumaisJ: Probabilistic Combination of Content and Links (STD, RJ), pp. 402–403.
SIGIR-2001-XuWN #information retrieval: Evaluating a Probabilistic Model for Cross-Lingual Information Retrieval (JX, RMW, CN), pp. 105–110.
POPL-2001-Monniaux #analysis #monte carlo #source code: An abstract Monte-Carlo method for the analysis of probabilistic programs (DM), pp. 93–101.
SAS-2001-Monniaux #analysis #source code #termination: An Abstract Analysis of the Probabilistic Termination of Programs (DM), pp. 111–126.
CC-2001-MehoferS #data flow #framework #novel: A Novel Probabilistic Data Flow Framework (EM, BS), pp. 37–51.
DAC-2001-BhanjaR #dependence #modelling #network #process #using: Dependency Preserving Probabilistic Modeling of Switching Activity using Bayesian Networks (SB, NR), pp. 209–214.
DAC-2001-GorenSW #analysis #novel #pipes and filters: A Novel Method for Stochastic Nonlinearity Analysis of a CMOS Pipeline ADC (DG, ES, IAW), pp. 127–132.
DAC-2001-LiouCKK #analysis #performance #statistics: Fast Statistical Timing Analysis By Probabilistic Event Propagation (JJL, KTC, SK, AK), pp. 661–666.
DATE-2001-MarculescuN #analysis #modelling: Probabilistic application modeling for system-level perfromance analysis (RM, AN), pp. 572–579.
PDP-2001-MehoferS #communication #optimisation #parallel: Probabilistic Communication Optimizations and Parallelization for Distributed-Memory Systems (EM, BS), p. 186–?.
ESOP-2001-Mitchell #analysis #calculus #polynomial #process #protocol #security: Probabilistic Polynomial-Time Process Calculus and Security Protocol Analysis (JCM), pp. 23–29.
ESOP-2001-Monniaux #abstract interpretation #source code: Backwards Abstract Interpretation of Probabilistic Programs (DM), pp. 367–382.
STOC-2001-Vatan #automaton: Distribution functions of probabilistic automata (FV), pp. 684–693.
TACAS-2001-AndovaB #abstraction #algebra #process: Abstraction in Probabilistic Process Algebra (SA, JCMB), pp. 204–219.
TACAS-2001-RuysLKLM #algebra #analysis #partial order #process #using: First Passage Time Analysis of Stochastic Process Algebra Using Partial Orders (TCR, RL, JPK, DL, MM), pp. 220–235.
ICLP-2001-Subrahmanian #database #logic programming: Probabilistic Databases and Logic Programming (VSS), p. 10.
LICS-2001-MitchellRST #analysis #calculus #process #protocol #security: Probabilistic Polynominal-Time Process Calculus and Security Protocol Analysis (JCM, AR, AS, VT), pp. 3–5.
SAT-2001-HuntMS #complexity #constraints #problem #quantifier: Complexity and Approximability of Quantified and Stochastic Constraint Satisfaction Problems (HBHI, MVM, RES), pp. 217–230.
SAT-2001-LynceBM #algorithm #satisfiability: Stochastic Systematic Search Algorithms for Satisfiability (IL, LB, JMS), pp. 190–204.
ADL-2000-ShatkayW #documentation #similarity: Finding Themes in Medline Documents: Probabilistic Similarity Search (HS, WJW), pp. 183–192.
ECDL-2000-OhtaTA #automaton #fuzzy #retrieval: Probabilistic Automaton Model for Fuzzy English-Text Retrieval (MO, AT, JA), pp. 35–44.
IFM-2000-HermannsKMS #algebra #model checking #process #towards: Towards Model Checking Stochastic Process Algebra (HH, JPK, JMK, MS), pp. 420–439.
ICML-2000-Eskin #detection #semistructured data #using: Anomaly Detection over Noisy Data using Learned Probability Distributions (EE), pp. 255–262.
ICML-2000-HuW #game studies: Experimental Results on Q-Learning for General-Sum Stochastic Games (JH, MPW), pp. 407–414.
ICML-2000-NikovskiN #learning #mobile #modelling #navigation: Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots (DN, IRN), pp. 671–678.
ICML-2000-Talavera #concept #feature model #incremental #learning: Feature Selection and Incremental Learning of Probabilistic Concept Hierarchies (LT), pp. 951–958.
ICML-2000-ThollardDH #automaton #using: Probabilistic DFA Inference using Kullback-Leibler Divergence and Minimality (FT, PD, CdlH), pp. 975–982.
ICPR-v2-2000-BaggenstossN #classification #using: A Theoretically Optimal Probabilistic Classifier Using Class-Specific Features (PMB, HN), pp. 2763–2768.
ICPR-v2-2000-BurrellP #algorithm #detection #learning #online #parametricity #process: Sequential Algorithms for Detecting Changes in Acting Stochastic Processes and On-Line Learning of their Operational Parameters (AB, TPK), pp. 2656–2659.
ICPR-v2-2000-VinokourovG #clustering #documentation: Probabilistic Hierarchical Clustering Method for Organizing Collections of Text Documents (AV, MG), pp. 2182–2185.
ICPR-v3-2000-GalambosKM #using: Using Gradient Information to Enhance the Progressive Probabilistic Hough Transform (CG, JK, JM), pp. 3564–3567.
ICPR-v3-2000-GomezSM #estimation: Probabilistic Estimation of Local Scale (GG, LES, JLM), pp. 3798–3801.
ICPR-v3-2000-NaphadeH #framework #semantics #using #video: Semantic Video Indexing Using a Probabilistic Framework (MRN, TSH), pp. 3083–3088.
ICPR-v3-2000-Ney #classification #modelling #recognition #speech: Stochastic Modeling: From Pattern Classification to Speech Recognition and Translation (HN), pp. 3025–3032.
ICPR-v3-2000-NodaK #adaptation #identification #using: Adaptive Speaker Identification Using Sequential Probability Ratio Test (HN, EK), pp. 3266–3269.
ICPR-v3-2000-OrriolsTBRVV #approach #detection #modelling #using: Probabilistic Saliency Approach for Elongated Structure Detection Using Deformable Models (XO, RT, XB, PR, JV, JJV), pp. 7018–7021.
ICPR-v3-2000-RoyG: MRF Solutions for Probabilistic Optical Flow Formulations (SR, VG), pp. 7053–7059.
ICPR-v3-2000-VaronaGRV #named #people: iTrack: Image-Based Probabilistic Tracking of People (XV, JG, FXR, JJV), pp. 7122–7125.
ICPR-v4-2000-BuiVW #framework: A Probabilistic Framework for Tracking in Wide-Area Environments (HHB, SV, GAWW), pp. 4702–4705.
ICPR-v4-2000-GilRS #approach #image #segmentation: Segmentation of artery wall in coronary IVUS images: A Probabilistic Approach (DG, PR, JS), pp. 4352–4355.
ICPR-v4-2000-Perez-CortesAAL #parsing: Stochastic Error-Correcting Parsing for OCR Post-Processing (JCPC, JCA, JA, RL), pp. 4405–4408.
KDD-2000-CadezGS #clustering #framework: A general probabilistic framework for clustering individuals and objects (IVC, SG, PS), pp. 140–149.
SIGIR-2000-AslamM: Bayes optimal metasearch: a probabilistic model for combining the results (JAA, MHM), pp. 379–381.
SIGIR-2000-Hofmann #learning #modelling #web: Learning probabilistic models of the Web (TH), pp. 369–371.
SIGIR-2000-PetasisCVPKS #adaptation #automation #machine learning: Automatic adaptation of proper noun dictionaries through cooperation of machine learning and probabilistic methods (GP, AC, PV, GP, VK, CDS), pp. 128–135.
PPDP-2000-Panangaden #logic #process: From logic to stochastic processes (PP), pp. 1–2.
PPDP-2000-PierroW #abstract interpretation #concurrent #constraints #programming #towards: Concurrent constraint programming: towards probabilistic abstract interpretation (ADP, HW), pp. 127–138.
SAS-2000-Monniaux #abstract interpretation #semantics: Abstract Interpretation of Probabilistic Semantics (DM), pp. 322–339.
DAC-2000-QiuWP #petri net #power management #using: Dynamic power management of complex systems using generalized stochastic Petri nets (QQ, QW, MP), pp. 352–356.
DATE-2000-DemirF #evaluation #modelling #performance: Stochastic Modeling and Performance Evaluation for Digital Clock and Data Recovery Circuits (AD, PF), pp. 340–344.
LCTES-2000-ChakravertyR #framework #realtime: A Stochastic Framework for Co-synthesis of Real-Time Systems (SC, CPR), pp. 96–113.
FoSSaCS-2000-BaierS #bisimulation: Norm Functions for Probabilistic Bisimulations with Delays (CB, MS), pp. 1–16.
FoSSaCS-2000-HerescuP #π-calculus: Probabilistic Asynchronous π-Calculus (OMH, CP), pp. 146–160.
STOC-2000-KatzY #encryption #security: Complete characterization of security notions for probabilistic private-key encryption (JK, MY), pp. 245–254.
STOC-2000-Klauck #communication #on the #protocol #quantum: On quantum and probabilistic communication: Las Vegas and one-way protocols (HK), pp. 644–651.
TACAS-2000-AlfaroKNPS #model checking #process #representation #using: Symbolic Model Checking of Probabilistic Processes Using MTBDDs and the Kronecker Representation (LdA, MZK, GN, DP, RS), pp. 395–410.
LICS-2000-DanosH #game studies #semantics: Probabilistic Game Semantics (VD, RH), pp. 204–213.
ICDAR-1999-NuijtG #recognition #towards: A Probabilistic Model for Postcode Recognition: A First Step towards Probabilistic Address Interpretation (MRN, EvG), pp. 761–764.
ICDAR-1999-StuckelbergD #on the #reasoning #recognition #using: On Musical Score Recognition using Probabilistic Reasoning (MVS, DSD), pp. 115–118.
VLDB-1999-DonjerkovicR #optimisation #query: Probabilistic Optimization of Top N Queries (DD, RR), pp. 411–422.
ICALP-1999-HassinP #distributed: Distributed Probabilistic Polling and Applications to Proportionate Agreement (YH, DP), pp. 402–411.
FM-v1-1999-LincolnMMS #analysis #equivalence #polynomial #security: Probabilistic Polynomial-Time Equivalence and Security Analysis (PL, JCM, MM, AS), pp. 776–793.
CIKM-1999-GovertLF #approach #categorisation #documentation #web: A Probabilistic Description-Oriented Approach for Categorizing Web Documents (NG, ML, NF), pp. 475–482.
CIKM-1999-LiY #classification #using: Text Classification Using ESC-based Stochastic Decision Lists (HL, KY), pp. 122–130.
ICML-1999-AbeL #concept #learning #linear #using: Associative Reinforcement Learning using Linear Probabilistic Concepts (NA, PML), pp. 3–11.
ICML-1999-ThrunLF #learning #markov #modelling #monte carlo #parametricity #process: Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes (ST, JL, DF), pp. 415–424.
SIGIR-1999-Ding #semantics #similarity: A Similarity-based Probability Model for Latent Semantic Indexing (CHQD), pp. 58–65.
SIGIR-1999-Hofmann #semantics: Probabilistic Latent Semantic Indexing (TH), pp. 50–57.
POPL-1999-GuptaJP #concurrent #constraints #process #source code: Stochastic Processes as Concurrent Constraint Programs (VG, RJ, PP), pp. 189–202.
ESEC-FSE-1999-Padberg: A Probabilistic Model for Software Projects (FP), pp. 109–126.
SAC-1999-LauberSW #assurance #online #quality #safety: Applied Probabilistic AI for Online Diagnosis of a Safety-Critical System Based on a Quality Assurance Program (JL, CS, RW), pp. 25–30.
FoSSaCS-1999-NarasimhaCI #calculus #logic #μ-calculus: Probabilistic Temporal Logics via the Modal μ-Calculus (MN, RC, SPI), pp. 288–305.
STOC-1999-CaiNS #theorem: Hardness and Hierarchy Theorems for Probabilistic Quasi-Polynomial Time (JyC, AN, DS), pp. 726–735.
TACAS-1999-GardnerL #realtime: Analyzing Stochastic Fixed-Priority Real-Time Systems (MKG, JWSL), pp. 44–58.
ICLP-1999-DekhtyarDS #logic programming #source code: Temporal Probabilistic Logic Programs (AD, MID, VSS), pp. 109–123.
ECDL-1998-Hiemstra #information retrieval #motivation: A Linguistically Motivated Probabilistic Model of Information Retrieval (DH), pp. 569–584.
PODS-1998-PapadimitriouRTV #analysis #semantics: Latent Semantic Indexing: A Probabilistic Analysis (CHP, PR, HT, SV), pp. 159–168.
VLDB-1998-Slutz #sql #testing: Massive Stochastic Testing of SQL (DRS), pp. 618–622.
ICALP-1998-Wigderson #algorithm #question: Do Probabilistic Algorithms Outperform Deterministic Ones? (AW), pp. 212–214.
ACIR-1998-PicardH #information retrieval #modelling: Modeling Information Retrieval with Probabilistic Argumentation Systems (JP, RH).
ACIR-1998-ZaragozaG #information management #information retrieval #modelling: Coupled Hierarchical IR and Stochastic Models for Surface Information Extraction (HZ, PG).
ICML-1998-KollerF #approximate #learning #process #using: Using Learning for Approximation in Stochastic Processes (DK, RF), pp. 287–295.
ICML-1998-MitaimK #adaptation #fuzzy: Stochastic Resonance with Adaptive Fuzzy Systems (SM, BK), pp. 377–385.
ICPR-1998-Aviles-Cruz #algorithm #data fusion #segmentation #using: Unsupervised texture segmentation using stochastic version of the EM algorithm and data fusion (CAC), pp. 1005–1009.
ICPR-1998-ChouS #relational: Probabilistic relational indexing (YYC, LGS), pp. 1331–1335.
ICPR-1998-HanKKL #network #segmentation: Temporal segmentation and selective attention in the stochastic oscillator neural network (SKH, WSK, HK, SWL), pp. 259–261.
ICPR-1998-IvinsPFO #component #linear: The joint probability density function for linear optic flow components (JI, JP, JPF, GAO), pp. 795–798.
ICPR-1998-Takasu #analysis #documentation #image: Probabilistic interpage analysis for article extraction from document images (AT), pp. 932–935.
KDD-1998-ChanGR #information retrieval #modelling: Probabilistic Modeling for Information Retrieval with Unsupervised Training Data (EPC, SG, SR), pp. 159–163.
KR-1998-Lukasiewicz #constraints #deduction: Probabilistic Deduction with Conditional Constraints over Basic Events (TL), pp. 380–393.
SIGIR-1998-Larson #retrieval: Cheshire II: Combining Probabilistic and Boolean Retrieval (RRL), p. 385.
SIGIR-1998-Picard #documentation #modelling #using: Modeling and Combining Evidence Provided by Document Relationships Using Probabilistic Argumentation Systems (JP), pp. 182–189.
SIGIR-1998-SmithS #algebra #named #web: PWA: An Extended Probabilistic Web Algebra (DS, RS), p. 388.
SAC-1998-Li #evaluation #performance: Performance evaluation of probabilistic tree embedding in cube-connected cycles (KL), pp. 584–592.
DAC-1998-KayP #named: PRIMO: Probability Interpretation of Moments for Delay Calculation (RK, LTP), pp. 463–468.
DAC-1998-VecianaJG #algorithm #constraints #performance: Hierarchical Algorithms for Assessing Probabilistic Constraints on System Performance (GdV, MFJ, JHG), pp. 251–256.
DATE-1998-MarculescuMP #estimation: Trace-Driven Steady-State Probability Estimation in FSMs with Application to Power Estimation (DM, RM, MP), pp. 774–779.
STOC-1998-CanettiMR: Perfectly One-Way Probabilistic Hash Functions (RC, DM, OR), pp. 131–140.
CSL-1998-Lukasiewicz #first-order #logic #semantics: Many-Valued First-Order Logics with Probabilistic Semantics (TL), pp. 415–429.
JICSLP-1998-Ruiz-AndinoR #integration #optimisation: Integration of CLP and Stochastic Optimisation Strategies (ARA, JJR), pp. 351–352.
LICS-1998-Alfaro #behaviour #how #verification: How to Specify and Verify the Long-Run Average Behavior of Probabilistic Systems (LdA), pp. 454–465.
LICS-1998-StarkS #analysis #automaton #composition #network: Compositional Analysis of Expected Delays in Networks of Probabilistic I/O Automata (EWS, SAS), pp. 466–477.
ECDL-1997-HardingCW #n-gram #retrieval #using: Probabilistic Retrieval of OCR Degraded Text Using N-Grams (SMH, WBC, CW), pp. 345–359.
ICDAR-1997-KangK #classification #framework #multi: Probabilistic Framework for Combining Multiple Classifiers at Abstract Level (HJK, JHK), pp. 870–874.
PODS-1997-NerjesMW #multi: Stochastic Service Guarantees for Continuous Data on Multi-Zone Disks (GN, PM, GW), pp. 154–160.
VLDB-1997-FlorescuKLP #integration #using: Using Probabilistic Information in Data Integration (DF, DK, AYL), pp. 216–225.
DLT-1997-PazC #array #automaton #evolution: Chaotic Evolution via Generalized Probabilistic Automata (Probabilistic Arrays) (AP, JWC), pp. 9–35.
DLT-1997-Zhiltsova #context-free grammar: An Optimal Coding for Stochastic Context-Free Languages with Unique Derivation (LPZ), pp. 539–550.
ICALP-1997-BaierCHKR #model checking #process: Symbolic Model Checking for Probabilistic Processes (CB, EMC, VHG, MZK, MR), pp. 430–440.
ICALP-1997-VinkR #algebra #approach #bisimulation: Bisimulation for Probabilistic Transition Systems: A Coalgebraic Approach (EPdV, JJMMR), pp. 460–470.
ICALP-1997-Weihrauch #metric #set: Computability on the Probability Measures on the Borel Sets of the Unit Interval (KW), pp. 166–176.
CIKM-1997-Lukasiewicz #deduction #knowledge base #performance #taxonomy: Efficient Global Probabilistic Deduction from Taxonomic and Probabilistic Knowledge-Bases over Conjunctive Events (TL), pp. 75–82.
ICML-1997-Gama #linear: Probabilistic Linear Tree (JG), pp. 134–142.
ICML-1997-Joachims #algorithm #analysis #categorisation: A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization (TJ), pp. 143–151.
KDD-1997-KeoghS #approach #database #pattern matching #performance: A Probabilistic Approach to Fast Pattern Matching in Time Series Databases (EJK, PS), pp. 24–30.
SIGIR-1997-Baumgarten #distributed #information retrieval: A Probabilistic Model for Distributed Information Retrieval (CB), pp. 258–266.
SIGIR-1997-GreiffCT #modelling: Computationally Tractable Probabilistic Modeling of Boolean Operators (WRG, WBC, HRT), pp. 119–128.
ICSE-1997-BernotBG #formal method #functional #testing: A Theory of Probabilistic Functional Testing (GB, LB, PLG), pp. 216–226.
ICSE-1997-KusumotoMKHTS #petri net: A New Software Project Simulator Based on Generalized Stochastic Petri-net (SK, OM, TK, YH, YT, KS), pp. 293–302.
DAC-1997-MarculescuMP #analysis #finite #sequence #state machine: Sequence Compaction for Probabilistic Analysis of Finite-State Machines (DM, RM, MP), pp. 12–15.
PDP-1997-OdorVR #automaton #parallel #simulation #string: Parallel simulation of ID probabilistic cellular automata on associative string processing machine (GÓ, GV, FR), pp. 149–154.
STOC-1997-FortnowS #linear: Retraction of Probabilistic Computation and Linear Time (LF, MS), p. 750.
TAPSOFT-1997-IyerN: Probabilistic Lossy Channel Systems (SPI, MN), pp. 667–681.
CAV-1997-BaierH #bisimulation #process: Weak Bisimulation for Fully Probabilistic Processes (CB, HH), pp. 119–130.
ICLP-1997-DekhtyarS #hybrid #source code: Hybrid Probabilistic Programs (AD, VSS), pp. 391–405.
ICALP-1996-BookVW #on the #quantifier: On Type-2 Probabilistic Quantifiers (RVB, HV, KWW), pp. 369–380.
ICFP-1996-ChuangH #approach #automation #data transformation #problem: A Probabilistic Approach to the Problem of Automatic Selection of Data Representations (TRC, WLH), pp. 190–200.
ICML-1996-LiuS #approach #feature model: A Probabilistic Approach to Feature Selection — A Filter Solution (HL, RS), pp. 319–327.
ICPR-1996-AstromH #analysis #detection #modelling: Stochastic modelling and analysis of sub-pixel edge detection (KÅ, AH), pp. 86–90.
ICPR-1996-AstromH96a #analysis: Stochastic analysis of scale-space smoothing (KÅ, AH), pp. 305–309.
ICPR-1996-Brailovsky #approach #detection: An approach to outlier detection based on Bayesian probabilistic model (VLB), pp. 70–74.
ICPR-1996-CharvillatT #3d #modelling: Registration of stereo-based 3D maps for object modeling: a stochastic yet intelligent solution (VC, BT), pp. 780–785.
ICPR-1996-KitamotoT #classification #image: A stochastic model of mixels and image classification (AK, MT), pp. 745–749.
ICPR-1996-OommenL #fault #pattern matching #pattern recognition #recognition: Probabilistic syntactic pattern recognition for traditional and generalized transposition errors (BJO, RKSL), pp. 685–689.
ICPR-1996-PulliS #modelling #recognition #using: Triplet-based object recognition using synthetic and real probability models (KP, LGS), pp. 75–79.
ICPR-1996-SchieleC #multi #recognition #using: Probabilistic object recognition using multidimensional receptive field histograms (BS, JLC), pp. 50–54.
PLILP-1996-StuckeyT #constraints #logic programming #modelling #theorem proving #using: Models for Using Stochastic Constraint Solvers in Constraint Logic Programming (PJS, VT), pp. 423–437.
DAC-1996-MarculescuMP #generative #sequence #synthesis: Stochastic Sequential Machine Synthesis Targeting Constrained Sequence Generation (DM, RM, MP), pp. 696–701.
TACAS-1996-HermannsMR #algebra #analysis #process: A Construction and Analysis Tool Based on the Stochastic Process Algebra TIPP (HH, VM, MR), pp. 427–430.
TACAS-1996-MoserM #automaton #realtime: Probabilistic Duration Automata for Analyzing Real-Time Systems (LEM, PMMS), pp. 369–390.
CAV-1996-Baier #algorithm #bisimulation #polynomial #simulation #testing: Polynomial Time Algorithms for Testing Probabilistic Bisimulation and Simulation (CB), pp. 50–61.
ICDAR-v1-1995-BertilleG #approach #automation: A probabilistic approach to automatic handwritten address reading (JMB, MG), pp. 368–371.
ICDAR-v1-1995-HoriuchiTYY #optimisation #process: Relaxation optimizing processes in extended probabilistic space (TH, KT, KY, HY), pp. 266–269.
ICDAR-v1-1995-OlivierPAL #modelling #recognition #using #word: Recognition of handwritten words using stochastic models (CO, TP, MA, YL), pp. 19–23.
ICDAR-v1-1995-SaonBG #modelling #recognition #word: Stochastic trajectory modeling for recognition of unconstrained handwritten words (GS, AB, YG), pp. 508–511.
ICALP-1995-NikoletseasRSY #graph #memory management: Stochastic Graphs Have Short Memory: Fully Dynamic Connectivity in Poly-Log Expected Time (SEN, JHR, PGS, MY), pp. 159–170.
ICML-1995-DaganE #classification: Committee-Based Sampling For Training Probabilistic Classifiers (ID, SPE), pp. 150–157.
ICML-1995-KimuraYK #learning: Reinforcement Learning by Stochastic Hill Climbing on Discounted Reward (HK, MY, SK), pp. 295–303.
SEKE-1995-Gattiker #functional #petri net #representation: Representing Structural and Functional Knowledge with Stochastic Petri Nets (JRG), pp. 47–53.
SIGIR-1995-CrestaniR #information retrieval: Probability Kinematics in Information Retrieval (FC, CJvR), pp. 291–299.
SIGIR-1995-Fuhr #datalog #logic #retrieval: Probabilistic Datalog — A Logic For Powerful Retrieval Methods (NF), pp. 282–290.
SIGIR-1995-MittendorfSS #library #scalability: Applying Probabilistic Term Weighting to OCR Text in the Case of a Large Alphabetic Library Catalogue (EM, PS, PS), pp. 328–335.
DAC-1995-FabbroFCG #modelling #standard #worst-case: An Assigned Probability Technique to Derive Realistic Worst-Case Timing Models of Digital Standard Cells (ADF, BF, LC, CG), pp. 702–706.
STOC-1995-AlurCY #nondeterminism #testing: Distinguishing tests for nondeterministic and probabilistic machines (RA, CC, MY), pp. 363–372.
STOC-1995-RaghavanU: Stochastic contention resolution with short delays (PR, EU), pp. 229–237.
TACAS-1995-Tofts #approximate #process: Analytic and Locally Approximate Solutions to Properties of Probabilistic Processes (CMNT), pp. 174–194.
CAV-1995-AzizSB #logic: It Usually Works: The Temporal Logic of Stochastic Systems (AA, VS, FB), pp. 155–165.
LICS-1995-Edalat #process: Domain Theory in Stochastic Processes (AE), pp. 244–254.
LICS-1995-JonssonY #composition #process #testing: Compositional Testing Preorders for Probabilistic Processes (BJ, WY), pp. 431–441.
ICALP-1994-Sanchez-CousoF #analysis #pattern matching: Average-Case Analysis of Pattern-Matching in Trees under the BST Probability Model (JRSC, MIFC), pp. 178–190.
ICALP-1994-Siegelmann #network #on the #power of: On The Computational Power of Probabilistic and Faulty Neural Networks (HTS), pp. 23–34.
ICML-1994-AbeM #predict: A New Method for Predicting Protein Secondary Structures Based on Stochastic Tree Grammars (NA, HM), pp. 3–11.
KDD-1994-TsumotoT #estimation #recursion: Selection of Probabilistic Measure Estimation Method Based on Recursive Iteration of Resampling Methods (ST, HT), pp. 121–132.
KR-1994-Jaeger #logic #reasoning: Probabilistic Reasoning in Terminological Logics (MJ), pp. 305–316.
KR-1994-KoenigS #graph: Risk-Sensitive Planning with Probabilistic Decision Graphs (SK, RGS), pp. 363–373.
SIGIR-1994-Cooper #information retrieval #question: The Formalism of Probability Theory in IR: A Foundation for An Encumbrance? (WSC), pp. 242–247.
SIGIR-1994-Gey #using: Inferring Probability of Relevance Using the Method of Logistic Regression (FCG), pp. 222–231.
SIGIR-1994-RobertsonW #approximate #effectiveness #retrieval: Some Simple Effective Approximations to the 2-Poisson Model for Probabilistic Weighted Retrieval (SER, SW), pp. 232–241.
SIGIR-1994-Sebastiani #information retrieval #logic #modelling: A Probabilistic Terminological Logic for Modelling Information Retrieval (FS0), pp. 122–130.
SIGIR-1994-TaghvaBC #information retrieval: Results of Applying Probabilistic IR to OCR Text (KT, JB, AC), pp. 202–211.
SAC-1994-AbualiSW #algorithm #design #network #search-based #using: Designing telecommunications networks using genetic algorithms and probabilistic minimum spanning trees (FNA, DAS, RLW), pp. 242–246.
SAC-1994-RaoI #approach #problem: A stochastic approach to the bin-packing problem (RLR, SSI), pp. 261–265.
DAC-1994-HachtelMPS #analysis #finite #scalability #state machine: Probabilistic Analysis of Large Finite State Machines (GDH, EM, AP, FS), pp. 270–275.
DAC-1994-MehrotraFL #approach #optimisation: Stochastic Optimization Approach to Transistor Sizing for CMOS VLSI Circuits (SM, PDF, WL), pp. 36–40.
EDAC-1994-AkitaA #logic #power management: A Method for Reducing Power Consumption of CMOS Logic Based on Signal Transition Probability (JA, KA), pp. 420–424.
EDAC-1994-XueDJ #analysis #fault #float: Probability Analysis for CMOS Floating Gate Faults (HX, CD, JAGJ), pp. 443–448.
STOC-1994-BellareGLR #approximate #performance #proving: Efficient probabilistic checkable proofs and applications to approximation (MB, SG, CL, AR), p. 820.
STOC-1994-ChariRS #algorithm #approximate: Improved algorithms via approximations of probability distributions (SC, PR, AS), pp. 584–592.
STOC-1994-CondonHPW #automaton #finite #nondeterminism #on the #power of: On the power of finite automata with both nondeterministic and probabilistic states (AC, LH, SP, AW), pp. 676–685.
STOC-1994-MacKenziePR #on the #protocol: On contention resolution protocols and associated probabilistic phenomena (PDM, CGP, RR), pp. 153–162.
ILPS-1994-LakshmananS #database #deduction: Probabilistic Deductive Databases (LVSL, FS), pp. 254–268.
ICDAR-1993-HongH #parsing #recognition: Text recognition enhancement with a probabilistic lattice chart parser (TH, JJH), pp. 222–225.
ICDAR-1993-KonnoH #algorithm #semantics: Postprocessing algorithm based on the probabilistic and semantic method for Japanese OCR (AK, YH), pp. 646–649.
ICDAR-1993-ParkL #modelling #multi #recognition: Large-set handwritten character recognition with multiple stochastic models (HSP, SWL), pp. 143–146.
DLT-1993-KrithivasanM #array #modelling #nondeterminism: Nondeterministic, Probabilistic and Alternating Computations on Cellular Array Models (KK, MM), pp. 342–354.
ICALP-1993-Ablayev #bound #communication #complexity: Lower Bounds for One-way Probabilistic Communication Complexity (FMA), pp. 241–252.
ICALP-1993-HagerupMM #maintenance: Maintaining Discrete Probability Distributions Optimally (TH, KM, JIM), pp. 253–264.
HCI-ACS-1993-Lewis #modelling #problem #usability: Problem Discovery in Usability Studies: A Models Based on the Binomial Probability Formula (JRL), pp. 666–671.
ICML-1993-Kaelbling #learning: Hierarchical Learning in Stochastic Domains: Preliminary Results (LPK), pp. 167–173.
ICML-1993-NortonH #learning: Learning DNF Via Probabilistic Evidence Combination (SWN, HH), pp. 220–227.
SIGIR-1993-Fuhr #database #information retrieval #integration #relational: A Probabilistic Relational Model for the Integration of IR and Databases (NF), pp. 309–317.
SAC-1993-AthertonL #comprehension #natural language: A Probabilistic Model for Natural Language Understanding (MA, DAL), pp. 586–592.
SAC-1993-Chen #fault #robust: Effect of Probabilistic Error Checking Procedures and Performability of Robust Objects (IRC), pp. 677–681.
SAC-1993-Sen #low cost #set #using: Minimal Cost Set Covering Using Probabilistic Methods (SS), pp. 157–164.
DAC-1993-StamoulisH #correlation #simulation: Improved Techniques for Probabilistic Simulation Including Signal Correlation Effects (GIS, INH), pp. 379–383.
ICALP-1992-CleavelandSZ #process #testing: Testing Preorders for Probabilistic Processes (RC, SAS, AEZ), pp. 708–719.
ICALP-1992-KirschenhoferPS #analysis #how #problem: How to Count Quickly and Accurately: A Unified Analysis of Probabilistic Counting and Other Related Problems (PK, HP, WS), pp. 211–222.
ML-1992-KononenkoK #generative #learning #multi #optimisation: Learning as Optimization: Stochastic Generation of Multiple Knowledge (IK, MK), pp. 257–262.
ML-1992-Mahadevan #learning #modelling: Enhancing Transfer in Reinforcement Learning by Building Stochastic Models of Robot Actions (SM), pp. 290–299.
SIGIR-1992-CooperGD #retrieval #staged: Probabilistic Retrieval Based on Staged Logistic Regression (WSC, FCG, DPD), pp. 198–210.
SIGIR-1992-Fuhr #integration #retrieval: Integration of Probabilistic Fact and Text Retrieval (NF), pp. 211–222.
SIGIR-1992-Nie #information retrieval #logic #semantics #towards: Towards a Probabilistic Modal Logic for Semantic-based Information Retrieval (JYN), pp. 140–151.
SIGMOD-1991-TsangarisN #approach #clustering: A Stochastic Approach for Clustering in Object Bases (MMT, JFN), pp. 12–21.
ICALP-1991-AlurCD #model checking #realtime: Model-Checking for Probabilistic Real-Time Systems (RA, CC, DLD), pp. 115–126.
ICALP-1991-KanepsF #automaton #regular expression: Running Time to Recognize Nonregular Languages by 2-Way Probabilistic Automata (JK, RF), pp. 174–185.
ICALP-1991-KannanY #generative: Program Checkers for Probability Generation (SK, ACCY), pp. 163–173.
KR-1991-Haddawy #logic #representation: A Temporal Probability Logic for Representing Actions (PH), pp. 313–324.
ML-1991-AllenT #concept #relational: Probabilistic Concept Formation in Relational Domains (JAA, KT), pp. 375–379.
ML-1991-BennettD: Comparing Stochastic Planning to the Acquisition of Increasingly Permissive Plans (SB, GD), pp. 586–590.
ML-1991-BhuyanR #adaptation #clustering #information retrieval: A Probabilistic Retrieval Scheme for Cluster-based Adaptive Information Retrieval (JNB, VVR), pp. 240–244.
ML-1991-desJardins #bias #learning: Probabilistic Evaluating of Bias for Learning Systems (Md), pp. 495–499.
ML-1991-YamanishiK #learning #search-based #sequence: Learning Stochastic Motifs from Genetic Sequences (KY, AK), pp. 467–471.
SIGIR-1991-Cooper #consistency #information retrieval #nondeterminism: Inconsistencies and Misnomers in Probabilistic IR (WSC), pp. 57–61.
SIGIR-1991-FuhrP: Combining Model-Oriented and Description-Oriented Approaches for Probabilistic Indexing (NF, UP), pp. 46–56.
SIGIR-1991-Lelu #algorithm #automation #generative #hypermedia #incremental #information retrieval: Automatic Generation of Hypertext Links in Information Retrieval Systems: A Stochastic and an Incremental Algorithm (AL), pp. 326–335.
DAC-1991-DeguchiIY #analysis #fault #logic: Probabilistic CTSS: Analysis of Timing Error Probability in Asynchronous Logic Circuits (YD, NI, SY), pp. 650–655.
DAC-1991-Najm #process: Transition Density, A Stochastic Measure of Activity in Digital Circuits (FNN), pp. 644–649.
DAC-1991-WuL #fault #testing: A Probabilistic Testability Measure for Delay Faults (WCW, CLL), pp. 440–445.
ADC-1991-Halpern #distributed: Knowledge and Probability in Distributed Systems (Abstract) (JYH), pp. 50–54.
STOC-1991-Karp: Probabilistic Recurrence Relations (RMK), pp. 190–197.
STOC-1991-MatiasV #parallel: Converting High Probability into Nearly-Constant Time-with Applications to Parallel Hashing (YM, UV), pp. 307–316.
CAV-1991-ChristoffC #algorithm #performance #process #verification: Efficient Algorithms for Verification of Equivalences for Probabilistic Processes (LC, IC), pp. 310–321.
CSL-1991-HeuschS #aspect-oriented #behaviour: Some Aspects of the Probabilistic Behavior of Variants of Resolution (PH, ES), pp. 164–172.
LICS-1991-JonssonL #process #refinement #specification: Specification and Refinement of Probabilistic Processes (BJ, KGL), pp. 266–277.
VLDB-1990-Fuhr #database #framework #query: A Probabilistic Framework for Vague Queries and Imprecise Information in Databases (NF), pp. 696–707.
ML-1990-ChanW #analysis #induction #learning #performance: Performance Analysis of a Probabilistic Inductive Learning System (KCCC, AKCW), pp. 16–23.
SIGIR-1990-FuhrB #documentation #feedback: Probabilistic Document Indexing from Relevance Feedback Data (NF, CB), pp. 45–61.
SIGIR-1990-FungCAT #architecture #concept #information retrieval: An Architecture for Probabilistic Concept-Based Information Retrieval (RMF, SLC, LAA, RMT), pp. 455–467.
DAC-1990-SaabR #effectiveness #evolution #heuristic #layout #performance #problem: Stochastic Evolution: a Fast Effective Heuristic for Some Generic Layout Problems (YS, VBR), pp. 26–31.
STOC-1990-NaorN #performance: Small-bias Probability Spaces: Efficient Constructions and Applications (JN, MN), pp. 213–223.
LICS-1990-GlabbeekSST #generative #modelling #process: Reactive, Generative, and Stratified Models of Probabilistic Processes (RJvG, SAS, BS, CMNT), pp. 130–141.
SIGMOD-1989-SalzaT #database #dependence #query #relational: Evaluating the Size of Queries on Relational Databases with non Uniform Distribution and Stochastic Dependence (SS, MT), pp. 8–14.
ICALP-1989-FeldmanM #algorithm: An Optimal Probabilistic Algorithm For Synchronous Byzantine Agreement (PF, SM), pp. 341–378.
ICALP-1989-LouchardRS #algorithm #analysis: Dynamic Algorithms in D. E. Knuth’s Model: A Probabilistic Analysis (GL, BR, RS), pp. 521–533.
KR-1989-Pearl #overview #reasoning #semantics: Probabilistic Semantics for Nonmonotonic Reasoning: A Survey (JP), pp. 505–516.
ML-1989-GoodmanS #algorithm #induction #set: The Induction of Probabilistic Rule Sets — The Itrule Algorithm (RMG, PS), pp. 129–132.
SIGIR-1989-Kwok #information retrieval #network: A Neural Network for Probabilistic Information Retrieval (KLK), pp. 21–30.
POPL-1989-LarsenS #bisimulation #testing: Bisimulation Through Probabilistic Testing (KGL, AS), pp. 344–352.
DAC-1989-Blanks #clustering: Partitioning by Probability Condensation (JB), pp. 758–761.
STOC-1989-FortnowS #linear: Probabilistic Computation and Linear Time (LF, MS), pp. 148–156.
LICS-1989-JonesP: A Probabilistic Powerdomain of Evaluations (CJ, GDP), pp. 186–195.
ICALP-1988-FlajoletGT #random: Random Allocations and Probabilistic Languages (PF, DG, LT), pp. 239–253.
SIGIR-1988-FuhrH #estimation: Optimum Probability Estimation Based on Expectations (NF, HH), pp. 257–273.
PPEALS-1988-Nicol #network #parallel #simulation: Parallel Discrete-Event Simulation Of FCFS Stochastic Queuing Networks (DMN), pp. 124–137.
VLDB-1987-CavalloP #database #formal method: The Theory of Probabilistic Databases (RC, MP), pp. 71–81.
ICALP-1987-LiY #complexity #parallel #symmetry: The Probabilistic and Deterministic Parallel Complexity of Symmetric Functions (ML, YY), pp. 326–335.
ICALP-1987-PittS #learning: Probability and Plurality for Aggregations of Learning Machines (LP, CHS), pp. 1–10.
SIGIR-1987-FuhrM: Probabilistic Search Term Weighting-Some Negative Results (NF, PM), pp. 13–18.
SIGIR-1987-OommenM #automaton #clustering #learning #performance #using: Fast Object Partitioning Using Stochastic Learning Automata (BJO, DCYM), pp. 111–122.
ICALP-1986-RosierY #complexity #concurrent #finite #on the #source code #termination: On The Complexity of Deciding Fair Termination of Probabilistic Concurrent Finite-State Programs (LER, HCY), pp. 334–343.
SIGIR-1986-Fuhr #modelling #retrieval: Two Models of Retrieval with Probabilistic Indexing (NF), pp. 249–257.
SIGIR-1986-LoseeBY #comparison #database #documentation #modelling #performance #retrieval: Probabilistic Models for Document Retrieval: A Comparison of Performance on Experimental and Synthetic Databases (RML, AB, CTY), pp. 258–264.
STOC-1986-Bern: Two Probabilistic Results on Rectilinear Steiner Trees (MWB), pp. 433–441.
STOC-1986-Cai #polynomial #random: With Probability One, A Random Oracle Separates PSPACE from the Polynomial-Time Hierarchy (JyC), pp. 21–29.
LICS-1986-PnueliZ #verification: Probabilistic Verification by Tableaux (AP, LDZ), pp. 322–331.
PODS-1985-BancilhonS #algebra #database #independence: Algebraic Versus Probabilistic Independence in Data Bases (FB, NS), pp. 149–153.
ICALP-1985-Jung #on the: On Probabilistic Time and Space (HJ), pp. 310–317.
ICALP-1985-KurtzM #algorithm #analysis #distributed #set: A Probabilistic Distributed Algorithm for Set Intersection and Its Analysis (TGK, UM), pp. 356–362.
SIGIR-1985-Bookstein #retrieval: Implications of Boolean Structures for Probabilistic Retrieval (AB), pp. 11–17.
SIGIR-1985-Kwok #automation #documentation #similarity: Experiments with Cited Titles for Automatic Document Indexing and Similarity Measure in a Probabilistic Context (KLK), pp. 165–178.
DAC-1985-RoseBT #analysis #design #performance #tool support: Integrating stochastic performance analysis with system design tools (CWR, MB, YT), pp. 482–488.
DAC-1985-Wunderlich #analysis #named #testing: PROTEST: a tool for probabilistic testability analysis (HJW), pp. 204–211.
STOC-1985-Clarkson #algorithm #problem: A Probabilistic Algorithm for the Post Office Problem (KLC), pp. 175–184.
ICALP-1984-Jung #complexity #matrix #on the #performance #problem: On Probabilistic Tape Complexity and Fast Circuits for Matrix Inversion Problems (HJ), pp. 281–291.
ICALP-1984-ReifS #distributed #resource management: Probabilistic Bidding Gives Optimal Distributed Resource Allocation (JHR, PGS), pp. 391–402.
SIGIR-1984-Kwok #feedback #retrieval #similarity: A Document-Document Similarity Measure Based on Cited Titles and Probability Theory, and Its Application to Relevance Feedback Retrieval (KLK), pp. 221–231.
STOC-1984-AjtaiB #constant #theorem: A Theorem on Probabilistic Constant Depth Computations (MA, MBO), pp. 471–474.
STOC-1984-HartS #bound #finite #logic #modelling: Probabilistic Temporal Logics for Finite and Bounded Models (SH, MS), pp. 1–13.
STOC-1984-KarpLM #analysis #multi #problem: A Probabilistic Analysis of Multidimensional Bin Packing Problems (RMK, ML, AMS), pp. 289–298.
STOC-1984-Upfal #modelling #parallel: A Probabilistic Relation between Desirable and Feasible Models of Parallel Computation (A Preliminary Version) (EU), pp. 258–265.
ICALP-1983-HartS #concurrent #how: Concurrent Probabilistic Program, or: How to Schedule if You Must (SH, MS), pp. 304–318.
STOC-1983-Feldman #decidability #logic: A Decidable Propositional Probabilistic Dynamic Logic (YAF), pp. 298–309.
STOC-1983-Kozen: A Probabilistic PDL (DK), pp. 291–297.
STOC-1983-Pnueli #algorithm #on the: On the Extremely Fair Treatment of Probabilistic Algorithms (AP), pp. 278–290.
STOC-1983-Turner #algorithm #analysis: Probabilistic Analysis of Bandwidth Minimization Algorithms (JST), pp. 467–476.
ICALP-1982-Reif #on the #parallel #power of: On the Power of Probabilistic Choice in Synchronous Parallel Computations (JHR), pp. 442–450.
SIGIR-1982-Maron #documentation #problem #retrieval: Probabilistic Approaches to the Document Retrieval Problem (MEM), pp. 98–107.
SIGIR-1982-RobertsonMC #information retrieval: The Unified Probabilistic Model for IR (SER, MEM, WSC), pp. 108–117.
POPL-1982-HartSP #concurrent #source code #termination: Termination of Probabilistic Concurrent Programs (SH, MS, AP), pp. 1–6.
STOC-1982-FeldmanH #logic: A Probabilistic Dynamic Logic (YAF, DH), pp. 181–195.
STOC-1982-GoldwasserM #encryption #game studies #how: Probabilistic Encryption and How to Play Mental Poker Keeping Secret All Partial Information (SG, SM), pp. 365–377.
STOC-1982-ManberT #nondeterminism: Probabilistic, Nondeterministic, and Alternating Decision Trees (UM, MT), pp. 234–244.
STOC-1982-Pippenger #simulation: Probabilistic Simulations (NP), pp. 17–26.
STOC-1982-RuzzoST #bound: Space-Bounded Hierarchies and Probabilistic Computations (WLR, JS, MT), pp. 215–223.
SIGIR-1981-YuL #approach #retrieval: An Approach to Probabilistic Retrieval (CTY, KL), pp. 46–55.
DAC-1981-WallaceH: Some properties of a probabilistic model for global wiring (DW, LH), pp. 660–667.
STOC-1981-Simon #bound #complexity #turing machine: Space-Bounded Probabilistic Turing Machine Complexity Classes Are Closed under Complement (JS), pp. 158–167.
SIGIR-1980-RobertsonRP #modelling: Probabilistic Models of Indexing and Searching (SER, CJvR, MFP), pp. 35–56.
SIGIR-1980-Weiss #algorithm #nearest neighbour: A Probabilistic Algorithm for Nearest Neighbour Searching (SFW), pp. 325–333.
STOC-1980-Reif #logic #programming: Logics for Probabilistic Programming (JHR), pp. 8–13.
ICALP-1979-Karp #algorithm #analysis #graph: Recent Advances in the Probabilistic Analysis of Graph-Theoretic Algorithms (RMK), pp. 338–339.
STOC-1978-Rackoff #algorithm: Relativized Questions Involving Probabilistic Algorithms (CR), pp. 338–342.
ICALP-1977-BertoniMT #automaton #problem #recursion: Some Recursive Unsolvable Problems Relating to Isolated Cutpoints in Probabilistic Automata (AB, GM, MT), pp. 87–94.
DAC-1977-Magnhagen #case study #design #experience #simulation: Practical experiences from signal probability simulation of digital designs (BM), pp. 216–219.
STOC-1977-AngluinV #algorithm #performance: Fast Probabilistic Algorithms for Hamiltonian Circuits and Matchings (DA, LGV), pp. 30–41.
SOSP-1975-ChandyR #execution #order #scheduling: Scheduling Partially Ordered Tasks with Probabilistic Execution Times (KMC, PFR), pp. 169–177.
STOC-1975-Fredman #sorting: Two Applications of a Probabilistic Search Technique: Sorting x + y and Building Balanced Search Trees (MLF), pp. 240–244.
STOC-1974-Gill #complexity #turing machine: Computational Complexity of Probabilistic Turing Machines (JTGI), pp. 91–95.
ICALP-1972-Bertoni #approximate #complexity #problem: Complexity Problems Related to the Approximation of Probabilistic Languages and Events by Deterministic Machines (AB), pp. 507–516.
STOC-1971-Santos #algebra: Algebraic Structure Theory of Stochastic Machines (ESS), pp. 219–243.
STOC-1970-Ellis #automaton: Probabilistic Tree Automata (CAE), pp. 198–205.