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markov
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Tag #markov

568 papers:

EDMEDM-2019-BoumiV #modelling #performance #student
Application of Hidden Markov Models to quantify the impact of enrollment patterns on student performance (SB, AV).
EDMEDM-2019-PolyzouNK #framework #recommendation
Scholars Walk: A Markov Chain Framework for Course Recommendation (AP, ANN, GK).
ICSMEICSME-2019-Alsuhaibani #identification #identifier #modelling
Applying Markov Models to Identify Grammatical Patterns of Function Identifiers (RSA), pp. 610–614.
SCAMSCAM-2019-HendersonPK #automation #fault #locality #process #using
Evaluating Automatic Fault Localization Using Markov Processes (TADH, AP, YK), pp. 115–126.
FMFM-2019-TapplerA0EL #learning #process
L*-Based Learning of Markov Decision Processes (MT, BKA, GB0, ME, KGL), pp. 651–669.
ECIRECIR-p1-2019-DijkFFK #approach #information retrieval
A Markovian Approach to Evaluate Session-Based IR Systems (DvD, MF, NF0, EK), pp. 621–635.
ICMLICML-2019-ChenBBGGMO #monte carlo
Stein Point Markov Chain Monte Carlo (WYC, AB, FXB, JG, MAG, LWM, CJO), pp. 1011–1021.
ICMLICML-2019-GeistSP #formal method #process
A Theory of Regularized Markov Decision Processes (MG, BS, OP), pp. 2160–2169.
ICMLICML-2019-JaberZB #equivalence #identification
Causal Identification under Markov Equivalence: Completeness Results (AJ, JZ, EB), pp. 2981–2989.
ICMLICML-2019-LimA #kernel #learning #process #robust
Kernel-Based Reinforcement Learning in Robust Markov Decision Processes (SHL, AA), pp. 3973–3981.
ICMLICML-2019-QuBT #graph #named #network
GMNN: Graph Markov Neural Networks (MQ, YB, JT0), pp. 5241–5250.
ICMLICML-2019-RadanovicDPS #learning #process
Learning to Collaborate in Markov Decision Processes (GR, RD, DCP, AS), pp. 5261–5270.
ICMLICML-2019-RosenbergM #online #optimisation #process
Online Convex Optimization in Adversarial Markov Decision Processes (AR0, YM), pp. 5478–5486.
ICMLICML-2019-WildnerK #process
Moment-Based Variational Inference for Markov Jump Processes (CW, HK), pp. 6766–6775.
KDDKDD-2019-0001S
Hidden Markov Contour Tree: A Spatial Structured Model for Hydrological Applications (ZJ0, AMS), pp. 804–813.
KDDKDD-2019-LiST #classification #higher-order #multi #network #predict #random
Multi-task Recurrent Neural Networks and Higher-order Markov Random Fields for Stock Price Movement Prediction: Multi-task RNN and Higer-order MRFs for Stock Price Classification (CL, DS, DT), pp. 1141–1151.
KDDKDD-2019-ShiZYLSJ #modelling #personalisation #sequence
State-Sharing Sparse Hidden Markov Models for Personalized Sequences (HS, CZ0, QY, YL0, FS, DJ), pp. 1549–1559.
QAPLQAPL-2019-PedersenBL #process
A Faster-Than Relation for Semi-Markov Decision Processes (MRP, GB, KGL), pp. 29–42.
ASPLOSASPLOS-2019-BanerjeeKI #algorithm #modelling #monte carlo #probability
AcMC 2 : Accelerating Markov Chain Monte Carlo Algorithms for Probabilistic Models (SSB, ZTK, RKI), pp. 515–528.
CASECASE-2019-BhatnagarSGB #process
Robotic Harvesting of a Moving Swarm Represented by a Markov Process (SB, SSS, JG, ATB), pp. 1157–1162.
CASECASE-2019-PengZZZ #analysis #component #detection #fault #kernel #multi #process
Hidden Markov Model Combined with Kernel Principal Component Analysis for Nonlinear Multimode Process Fault Detection (PP, JZ, YZ, HZ), pp. 1586–1591.
CAVCAV-2019-AshokKW #game studies #model checking #probability #process #statistics
PAC Statistical Model Checking for Markov Decision Processes and Stochastic Games (PA, JK, MW), pp. 497–519.
EDMEDM-2018-HoernleGGPR #interactive #modelling #simulation #student #using
Modeling the Effects of Students' Interactions with Immersive Simulations using Markov Switching Systems (NH, YG, BJG, PP, AR).
CoGCIG-2018-StreckW #animation #using
Using Discrete Time Markov Chains for Control of Idle Character Animation (AS, TW), pp. 1–4.
ICMLICML-2018-BacciuEM #approach #generative #graph
Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing (DB, FE, AM), pp. 304–313.
ICMLICML-2018-Huang0S #learning #modelling #topic
Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling (KH, XF0, NDS), pp. 2073–2082.
ICMLICML-2018-Kim #modelling #process
Markov Modulated Gaussian Cox Processes for Semi-Stationary Intensity Modeling of Events Data (MK), pp. 2645–2653.
ICMLICML-2018-LiWZ #estimation
Estimation of Markov Chain via Rank-constrained Likelihood (XL, MW, AZ), pp. 3039–3048.
ICMLICML-2018-MetelliMR #configuration management #process
Configurable Markov Decision Processes (AMM, MM, MR), pp. 3488–3497.
KDDKDD-2018-AcharyaGZ #topic
A Dual Markov Chain Topic Model for Dynamic Environments (AA, JG, MZ), pp. 1099–1108.
KDDKDD-2018-Xie0S
Geographical Hidden Markov Tree for Flood Extent Mapping (MX, ZJ0, AMS), pp. 2545–2554.
ICSE-2018-HabayebMMB #debugging #on the #predict #using
On the use of hidden Markov model to predict the time to fix bugs (MH, SSM, AVM, ABB), p. 700.
CASECASE-2018-LiXPC #performance #probability
Efficient Sampling Procedure for Selecting the Largest Stationary Probability of a Markov Chain (HL, XX, YP, CHC), pp. 899–905.
CASECASE-2018-SarkaleNCEM #optimisation #process #simulation
Solving Markov decision processes for network-level post-hazard recovery via simulation optimization and rollout (YS, SN, EKPC, BRE, HM), pp. 906–912.
ESOPESOP-2018-0001BBBG0 #probability #reasoning #relational #λ-calculus
Relational Reasoning for Markov Chains in a Probabilistic Guarded Lambda Calculus (AA0, GB, LB, AB, MG, DG0), pp. 214–241.
CAVCAV-2018-TangB #distance #probability #similarity
Deciding Probabilistic Bisimilarity Distance One for Labelled Markov Chains (QT0, FvB), pp. 681–699.
CAVCAV-2018-ChatterjeeHLOT #algorithm #graph #process
Symbolic Algorithms for Graphs and Markov Decision Processes with Fairness Objectives (KC, MH, VL, SO, VT), pp. 178–197.
ICSAICSA-2017-CalinescuCGKP #design #parametricity #robust #synthesis
Designing Robust Software Systems through Parametric Markov Chain Synthesis (RC, MC0, SG, MK, NP), pp. 131–140.
ICSAICSA-2017-PatersonC #analysis #quality #refinement
Accurate Analysis of Quality Properties of Software with Observation-Based Markov Chain Refinement (CP, RC), pp. 121–130.
EDMEDM-2017-GeigleZ #behaviour #modelling #student
Modeling MOOC Student Behavior With Two-Layer Hidden Markov Models (CG, CZ).
EDMEDM-2017-PokrajacSYH #modelling #using
Modeling Dormitory Occupancy Using Markov Chains (DDP, KS, DY, TH).
ICMLICML-2017-DawsonHM #infinity
An Infinite Hidden Markov Model With Similarity-Biased Transitions (CRD, CH, CTM), pp. 942–950.
ICMLICML-2017-Hoffman #learning #modelling #monte carlo
Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo (MDH), pp. 1510–1519.
ICMLICML-2017-MaFF #modelling #probability
Stochastic Gradient MCMC Methods for Hidden Markov Models (YAM, NJF, EBF), pp. 2265–2274.
ICMLICML-2017-Simsekli #difference #equation #monte carlo #probability
Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for Markov Chain Monte Carlo (US), pp. 3200–3209.
KDDKDD-2017-WuG #higher-order #process
Retrospective Higher-Order Markov Processes for User Trails (TW, DFG), pp. 1185–1194.
PLDIPLDI-2017-HuangTM #algorithm #compilation #modelling #monte carlo #probability
Compiling Markov chain Monte Carlo algorithms for probabilistic modeling (DH0, JBT, GM), pp. 111–125.
SASSAS-2017-OuadjaoutM #communication #protocol #static analysis #using
Quantitative Static Analysis of Communication Protocols Using Abstract Markov Chains (AO, AM), pp. 277–298.
ICSE-2017-SuCFR #evaluation #named #performance #runtime
ProEva: runtime proactive performance evaluation based on continuous-time markov chains (GS, TC, YF0, DSR), pp. 484–495.
CASECASE-2017-BaeM #multi #random
Markovian property for the delays in multiclass deterministic flow lines with random arrivals (SYB, JRM), pp. 729–730.
CASECASE-2017-ChenGL #analysis #identification #online #performance
Load identification based on Factorial Hidden Markov Model and online performance analysis (SC, FG, TL0), pp. 1249–1253.
CASECASE-2017-KinghorstGLCYFZ #algorithm #approach #maintenance #modelling #predict #search-based
Hidden Markov model-based predictive maintenance in semiconductor manufacturing: A genetic algorithm approach (JK, OG, ML, HLC, KY, JF, MZ, BVH), pp. 1260–1267.
CASECASE-2017-MazakWP #process #reverse engineering
Reverse engineering of production processes based on Markov chains (AM, MW, PPB), pp. 680–686.
CASECASE-2017-WangFFLC #energy #probability
Markov chain based idle status control of stochastic machines for energy saving operation (JW, YF, ZF, SL, QC), pp. 1019–1023.
CAVCAV-2017-AshokCDKM #process
Value Iteration for Long-Run Average Reward in Markov Decision Processes (PA, KC, PD, JK, TM), pp. 201–221.
CAVCAV-2017-Baier0L0W #model checking #process #reliability
Ensuring the Reliability of Your Model Checker: Interval Iteration for Markov Decision Processes (CB, JK0, LL, DP0, SW), pp. 160–180.
CAVCAV-2017-QuatmannJK #automaton #multi
Markov Automata with Multiple Objectives (TQ, SJ, JPK), pp. 140–159.
EDMEDM-2016-FauconKD #simulation #student
Semi-Markov model for simulating MOOC students (LF, LK, PD), pp. 358–363.
EDMEDM-2016-TissenbaumBK #behaviour #game studies #modelling #visitor
Modeling Visitor Behavior in a Game-Based Engineering Museum Exhibit with Hidden Markov Models (MT, MB, VK), pp. 517–522.
EDMEDM-2016-Yee-Kingd #collaboration #learning #online #process #social
Stimulating collaborative activity in online social learning environments with Markov decision processes (MYK, Md), pp. 652–653.
MSRMSR-2016-DamevskiCSP #developer #interactive #using
Interactive exploration of developer interaction traces using a hidden markov model (KD, HC0, DCS, LLP), pp. 126–136.
FSCDFSCD-2016-CoquandM #independence #type system
The Independence of Markov's Principle in Type Theory (TC, BM), p. 18.
CoGCIG-2016-TamassiaRSDZH #approach #game studies #modelling #online #predict
Predicting player churn in destiny: A Hidden Markov models approach to predicting player departure in a major online game (MT, WLR, RS, AD, FZ, MH), pp. 1–8.
CIKMCIKM-2016-RongZYSL #approach #optimisation #performance #process
The Rich and the Poor: A Markov Decision Process Approach to Optimizing Taxi Driver Revenue Efficiency (HR, XZ, CY, MZS, AXL), pp. 2329–2334.
ICMLICML-2016-GuanRW #learning #multi #performance #process #recognition #using
Efficient Multi-Instance Learning for Activity Recognition from Time Series Data Using an Auto-Regressive Hidden Markov Model (XG, RR, WKW), pp. 2330–2339.
ICMLICML-2016-LiuSSF #learning #network
Structure Learning of Partitioned Markov Networks (SL0, TS, MS, KF), pp. 439–448.
ICMLICML-2016-PerolatPGSP #approximate #game studies #policy
Softened Approximate Policy Iteration for Markov Games (JP, BP, MG, BS, OP), pp. 1860–1868.
ICMLICML-2016-RainforthNLPMDW #monte carlo
Interacting Particle Markov Chain Monte Carlo (TR, CAN, FL, BP, JWvdM, AD, FDW), pp. 2616–2625.
ICMLICML-2016-ZhangP #feature model #modelling
Markov Latent Feature Models (AZ, JWP), pp. 1129–1137.
ICPRICPR-2016-DuWZH #network #recognition
Deep neural network based hidden Markov model for offline handwritten Chinese text recognition (JD, ZRW, JFZ, JSH), pp. 3428–3433.
ICPRICPR-2016-GaoJ #hybrid
Hybrid Markov Blanket discovery (TG, QJ), pp. 1653–1658.
ICPRICPR-2016-KimKAK #modelling #process #recognition
Integrating hidden Markov models based on Mixture-of-Templates and k-NN2 ensemble for activity recognition (YJK, YK, JA, DK0), pp. 1636–1641.
KDDKDD-2016-MelnykBMO #detection #modelling
Semi-Markov Switching Vector Autoregressive Model-Based Anomaly Detection in Aviation Systems (IM, AB, BLM, NCO), pp. 1065–1074.
CASECASE-2016-LeeLMB #community
A Markov chain model to evaluate patient transitions in small community hospitals (HKL, JL, AJM, PAB), pp. 675–680.
FASEFASE-2016-SuCFRT #adaptation #process #self
An Iterative Decision-Making Scheme for Markov Decision Processes and Its Application to Self-adaptive Systems (GS, TC, YF0, DSR, PST), pp. 269–286.
CAVCAV-2016-BaierK0K0W #ambiguity #automaton
Markov Chains and Unambiguous Büchi Automata (CB, SK, JK0, SK, DM0, JW0), pp. 23–42.
CSLCSL-2016-AlurFKS #process
Hedging Bets in Markov Decision Processes (RA, MF, SK, NS), p. 20.
VMCAIVMCAI-2016-DelahayeLP #parametricity #synthesis
Parameter Synthesis for Parametric Interval Markov Chains (BD, DL, LP), pp. 372–390.
SCAMSCAM-J-2013-CeruloPBCC15 #detection #named
Irish: A Hidden Markov Model to detect coded information islands in free text (LC, MDP, AB, MC, GC), pp. 26–43.
ICALPICALP-v2-2015-EtessamiSY #branch #equation #fixpoint #polynomial #probability #process #reachability
Greatest Fixed Points of Probabilistic Min/Max Polynomial Equations, and Reachability for Branching Markov Decision Processes (KE, AS, MY), pp. 184–196.
ICEISICEIS-v2-2015-FrantzSRYE #ecosystem #integration #on the #process #using
On using Markov Decision Processes to Model Integration Solutions for Disparate Resources in Software Ecosystems (RZF, SS, FRF, IY, MTME), pp. 260–267.
CIKMCIKM-2015-YeL #constraints #logic #multi #network
Structural Constraints for Multipartite Entity Resolution with Markov Logic Network (TY, HWL), pp. 1691–1694.
ICMLICML-2015-Abbasi-YadkoriB #crowdsourcing #problem #scalability
Large-Scale Markov Decision Problems with KL Control Cost and its Application to Crowdsourcing (YAY, PLB, XC, AM), pp. 1053–1062.
ICMLICML-2015-GornitzBK #detection
Hidden Markov Anomaly Detection (NG, MLB, MK), pp. 1833–1842.
ICMLICML-2015-HugginsNSM #named #process
JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes (JHH, KN, AS, VKM), pp. 693–701.
ICMLICML-2015-JerniteRS #approach #learning #modelling #performance #random
A Fast Variational Approach for Learning Markov Random Field Language Models (YJ, AMR, DS), pp. 2209–2217.
ICMLICML-2015-Osogami #process #robust
Robust partially observable Markov decision process (TO), pp. 106–115.
ICMLICML-2015-PerolatSPP #approximate #game studies #programming
Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games (JP, BS, BP, OP), pp. 1321–1329.
ICMLICML-2015-SalimansKW #monte carlo
Markov Chain Monte Carlo and Variational Inference: Bridging the Gap (TS, DPK, MW), pp. 1218–1226.
ICMLICML-2015-TanseyPSR #exponential #product line #random
Vector-Space Markov Random Fields via Exponential Families (WT, OHMP, ASS, PR), pp. 684–692.
ICMLICML-2015-ZhangP #modelling
Markov Mixed Membership Models (AZ, JP), pp. 475–483.
KDDKDD-2015-YuW0PSIW #bound #multi
Tornado Forecasting with Multiple Markov Boundaries (KY, DW, WD, JP, DLS, SI, XW), pp. 2237–2246.
RecSysRecSys-2015-AghdamHMB #adaptation #modelling #recommendation #using
Adapting Recommendations to Contextual Changes Using Hierarchical Hidden Markov Models (MHA, NH, BM, RDB), pp. 241–244.
SEKESEKE-2015-AssuncaoFLSV #automaton #generative #modelling #named #network #predict #probability
SANGE — Stochastic Automata Networks Generator. A tool to efficiently predict events through structured Markovian models (JA, PF, LL, AS, JMV), pp. 581–584.
SIGIRSIGIR-2015-LiDDCZB #behaviour #process #query
Analyzing User’s Sequential Behavior in Query Auto-Completion via Markov Processes (LL, HD, AD, YC, HZ, RABY), pp. 123–132.
QAPLQAPL-2015-AldiniB #automaton #similarity
Expected-Delay-Summing Weak Bisimilarity for Markov Automata (AA, MB), pp. 1–15.
QAPLQAPL-2015-BortolussiH #modelling #performance
Efficient Checking of Individual Rewards Properties in Markov Population Models (LB, JH), pp. 32–47.
QAPLQAPL-2015-BortolussiNGGHL #adaptation #named
CARMA: Collective Adaptive Resource-sharing Markovian Agents (LB, RDN, VG, SG, JH, DL, ML, MM), pp. 16–31.
ASEASE-2015-NguyenPVN #api #mobile #recommendation
Recommending API Usages for Mobile Apps with Hidden Markov Model (TTN, HVP, PMV, TTN), pp. 795–800.
SACSAC-2015-Homm0G #concurrent #modelling #statistics #testing
Concurrent streams in Markov chain usage models for statistical testing of complex systems (DH, JE, RG), pp. 1803–1807.
CASECASE-2015-BaeM #modelling #multi #random
Markovian modeling of multiclass deterministic flow lines with random arrivals: The case of a single-channel (SYB, JRM), pp. 649–654.
CASECASE-2015-ParisACAR #behaviour #learning #smarttech #using
Using Hidden Semi-Markov Model for learning behavior in smarthomes (AP, SA, NC, AEA, NR), pp. 752–757.
CASECASE-2015-ZhangTYL #assessment #reliability #using
CAN node reliability assessment using segmented discrete time Markov chains (LZ, LT, FY, YL), pp. 231–236.
DACDAC-2015-ZaheerWGL #named #performance #process
mTunes: efficient post-silicon tuning of mixed-signal/RF integrated circuits based on Markov decision process (MZ, FW, CG, XL), p. 6.
FoSSaCSFoSSaCS-2015-BacciBLM #distance #on the
On the Total Variation Distance of Semi-Markov Chains (GB, GB, KGL, RM), pp. 185–199.
STOCSTOC-2015-Louis #algorithm #approximate
Hypergraph Markov Operators, Eigenvalues and Approximation Algorithms (AL), pp. 713–722.
CAVCAV-2015-AbateBCK #adaptation #analysis #network
Adaptive Aggregation of Markov Chains: Quantitative Analysis of Chemical Reaction Networks (AA, LB, MC, MZK), pp. 195–213.
CAVCAV-2015-BrazdilCCFK #learning #process
Counterexample Explanation by Learning Small Strategies in Markov Decision Processes (TB, KC, MC, AF, JK), pp. 158–177.
CAVCAV-2015-RandourRS #multi #process #query
Percentile Queries in Multi-dimensional Markov Decision Processes (MR, JFR, OS), pp. 123–139.
ICLPICLP-2015-LeeMW #logic #semantics
Markov Logic Style Weighted Rules under the Stable Model Semantics (JL, YM, YW), pp. 207–220.
LICSLICS-2015-ChatterjeeKK #multi #process
Unifying Two Views on Multiple Mean-Payoff Objectives in Markov Decision Processes (KC, ZK, JK), pp. 244–256.
LICSLICS-2015-McIverMR #data flow #modelling #monad
Abstract Hidden Markov Models: A Monadic Account of Quantitative Information Flow (AM, CM, TMR), pp. 597–608.
VMCAIVMCAI-2015-BraitlingFHWBH #automaton #metric
Abstraction-Based Computation of Reward Measures for Markov Automata (BB, LMFF, HH, RW, BB, HH), pp. 172–189.
VMCAIVMCAI-2015-SahaEJMT #distributed
Distributed Markov Chains (RS, JE, SKJ, MM, PST), pp. 117–134.
DRRDRR-2014-WuZCLN #framework #recognition #segmentation
A Markov chain based line segmentation framework for handwritten character recognition (YW, SZ, HC, DL, PN), p. ?–12.
ICALPICALP-v1-2014-CzumajV
Thorp Shuffling, Butterflies, and Non-Markovian Couplings (AC, BV), pp. 344–355.
SFMSFM-2014-AbrahamBDJKW #generative #modelling #overview
Counterexample Generation for Discrete-Time Markov Models: An Introductory Survey (, BB, CD, NJ, JPK, RW), pp. 65–121.
AIIDEAIIDE-2014-SnodgrassO #approach #generative #using
A Hierarchical Approach to Generating Maps Using Markov Chains (SS, SO).
CoGCIG-2014-LeeceJ #game studies #modelling #random #using
Opponent state modeling in RTS games with limited information using Markov random fields (MAL, AJ), pp. 1–7.
FDGFDG-2014-SnodgrassO #generative #using
Experiments in map generation using Markov chains (SS, SO).
HCIHCI-AIMT-2014-RoyC #artificial reality #detection #invariant #using
View-Invariant Human Detection from RGB-D Data of Kinect Using Continuous Hidden Markov Model (SR, TC), pp. 325–336.
HCILCT-NLE-2014-TaraghiSES #classification #learning #multi
Markov Chain and Classification of Difficulty Levels Enhances the Learning Path in One Digit Multiplication (BT, AS, ME, MS), pp. 322–333.
CAiSECAiSE-2014-StulpnagelOS #logic #network #risk management
IT Risk Management with Markov Logic Networks (JvS, JO, JS), pp. 301–315.
CAiSECAiSE-2014-VergneS #community #network #open source #using
Expert Finding Using Markov Networks in Open Source Communities (MV, AS), pp. 196–210.
ICMLICML-c1-2014-BardenetDH #adaptation #approach #monte carlo #scalability #towards
Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach (RB, AD, CCH), pp. 405–413.
ICMLICML-c1-2014-DickGS #learning #online #process #sequence
Online Learning in Markov Decision Processes with Changing Cost Sequences (TD, AG, CS), pp. 512–520.
ICMLICML-c1-2014-HajiaghayiKWB #estimation #performance
Efficient Continuous-Time Markov Chain Estimation (MH, BK, LW, ABC), pp. 638–646.
ICMLICML-c1-2014-LianREC #correlation #modelling #process
Modeling Correlated Arrival Events with Latent Semi-Markov Processes (WL, VR, BE, LC), pp. 396–404.
ICMLICML-c1-2014-ZhangZZ #infinity #modelling
Max-Margin Infinite Hidden Markov Models (AZ, JZ, BZ), pp. 315–323.
ICMLICML-c2-2014-CelikkayaS #probability #process
Deterministic Anytime Inference for Stochastic Continuous-Time Markov Processes (EBC, CRS), pp. 1962–1970.
ICMLICML-c2-2014-MalekAB #linear #problem #programming #scalability
Linear Programming for Large-Scale Markov Decision Problems (AM, YAY, PLB), pp. 496–504.
ICMLICML-c2-2014-McGibbonRSKP #comprehension #modelling
Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models (RM, BR, MS, GK, VSP), pp. 1197–1205.
ICMLICML-c2-2014-MizrahiDF #learning #linear #parallel #random
Linear and Parallel Learning of Markov Random Fields (YDM, MD, NdF), pp. 199–207.
ICPRICPR-2014-KaradagV #image #random
Fusion of Image Segmentations under Markov, Random Fields (ÖÖK, FTYV), pp. 930–935.
ICPRICPR-2014-SinghKZ #detection #difference #image #multi #scalability
A Multilayer Markovian Model for Change Detection in Aerial Image Pairs with Large Time Differences (PS, ZK, JZ), pp. 924–929.
ICPRICPR-2014-WangCH #hybrid #multi #random #using #video
Wide Baseline Multi-view Video Matting Using a Hybrid Markov Random Field (TW, JPC, AH), pp. 136–141.
ICPRICPR-2014-WangWJ14a #modelling #recognition #using
Early Facial Expression Recognition Using Hidden Markov Models (JW, SW, QJ), pp. 4594–4599.
ICPRICPR-2014-ZhaoSJ #classification
Coupled Hidden Markov Model for Electrocorticographic Signal Classification (RZ, GS, QJ), pp. 1858–1862.
MLDMMLDM-2014-JiangDPL #approach #estimation #optimisation #recognition
Modified Bootstrap Approach with State Number Optimization for Hidden Markov Model Estimation in Small-Size Printed Arabic Text Line Recognition (ZJ, XD, LP, CL), pp. 437–441.
SIGIRSIGIR-2014-FerranteFM #injection #modelling #precise
Injecting user models and time into precision via Markov chains (MF, NF, MM), pp. 597–606.
QAPLQAPL-2014-BraitlingFHWBH #abstraction #automaton #game studies #named #refinement
MeGARA: Menu-based Game Abstraction and Abstraction Refinement of Markov Automata (BB, LMFF, HH, RW, BB, HH), pp. 48–63.
QAPLQAPL-2014-SpielerHZ #model checking #modelling
Model Checking CSL for Markov Population Models (DS, EMH, LZ), pp. 93–107.
CASECASE-2014-ChenS #approach #modelling #novel #using
Modeling building occupancy using a novel inhomogeneous Markov chain approach (ZC, YCS), pp. 1079–1084.
CASECASE-2014-FeyzabadiC #process #using
Risk-aware path planning using hirerachical constrained Markov Decision Processes (SF, SC), pp. 297–303.
CASECASE-2014-HaoLGC #effectiveness #flexibility #network #nondeterminism #problem #scheduling
An effective Markov network based EDA for flexible job shop scheduling problems under uncertainty (XCH, LL, MG, CFC), pp. 131–136.
CASECASE-2014-LuXJ #process
A Markov Decision Process model for elective inpatient admission with delay announcement (YL, XX, ZJ), pp. 552–557.
FoSSaCSFoSSaCS-2014-0001MS #process
Limit Synchronization in Markov Decision Processes (LD, TM, MS), pp. 58–72.
FoSSaCSFoSSaCS-2014-Fu #bound #probability #process #reachability
Maximal Cost-Bounded Reachability Probability on Continuous-Time Markov Decision Processes (HF), pp. 73–87.
TACASTACAS-2014-BaierKKM #modelling
Computing Conditional Probabilities in Markovian Models Efficiently (CB, JK, SK, SM), pp. 515–530.
TACASTACAS-2014-SoudjaniA #approximate #precise #probability #process
Precise Approximations of the Probability Distribution of a Markov Process in Time: An Application to Probabilistic Invariance (SEZS, AA), pp. 547–561.
LICSLICS-CSL-2014-ChenK #distance #on the
On the total variation distance of labelled Markov chains (TC, SK), p. 10.
VMCAIVMCAI-2014-Song0G #bisimulation #logic #process
Bisimulations and Logical Characterizations on Continuous-Time Markov Decision Processes (LS, LZ, JCG), pp. 98–117.
DRRDRR-2013-TaghvaPM #higher-order #modelling
Post processing with first- and second-order hidden Markov models (KT, SP, SM).
ICDARICDAR-2013-ElzobiADES #adaptation #approach #modelling #recognition
A Hidden Markov Model-Based Approach with an Adaptive Threshold Model for Off-Line Arabic Handwriting Recognition (ME, AAH, LD, ME, AS), pp. 945–949.
ICDARICDAR-2013-ZhouTLW #random #recognition #using
Minimum Risk Training for Handwritten Chinese/Japanese Text Recognition Using Semi-Markov Conditional Random Fields (XDZ, FT, CLL, HW), pp. 940–944.
SIGMODSIGMOD-2013-CaiVPAHJ #simulation #using
Simulation of database-valued markov chains using SimSQL (ZC, ZV, LLP, SA, PJH, CMJ), pp. 637–648.
VLDBVLDB-2013-0002GJ #correlation #modelling #using
Travel Cost Inference from Sparse, Spatio-Temporally Correlated Time Series Using Markov Models (BY, CG, CSJ), pp. 769–780.
SCAMSCAM-2013-CeruloCPC #detection
A Hidden Markov Model to detect coded information islands in free text (LC, MC, MDP, GC), pp. 157–166.
LATALATA-2013-BiondiLNW #process
Maximizing Entropy over Markov Processes (FB, AL, BFN, AW), pp. 128–140.
SFMSFM-2013-BortolussiH #approximate #behaviour #modelling
Checking Individual Agent Behaviours in Markov Population Models by Fluid Approximation (LB, JH), pp. 113–149.
ICMLICML-c1-2013-WilliamsonDX #modelling #monte carlo #parallel #parametricity
Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models (SW, AD, EPX), pp. 98–106.
ICMLICML-c1-2013-WulsinFL #correlation #parsing #process #using
Parsing epileptic events using a Markov switching process model for correlated time series (DW, EBF, BL), pp. 356–364.
ICMLICML-c2-2013-MeentBWGW #learning #modelling
Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data (JWvdM, JEB, FW, RLG, CW), pp. 361–369.
ICMLICML-c3-2013-HuangS #learning #modelling
Spectral Learning of Hidden Markov Models from Dynamic and Static Data (TKH, JGS), pp. 630–638.
ICMLICML-c3-2013-KolarLX #estimation #multi #network
Markov Network Estimation From Multi-attribute Data (MK, HL, EPX), pp. 73–81.
KDDKDD-2013-HallakCM #process
Model selection in markovian processes (AH, DDC, SM), pp. 374–382.
RecSysRecSys-2013-AlanaziB #modelling #recommendation #using
A people-to-people content-based reciprocal recommender using hidden markov models (AA, MB), pp. 303–306.
SIGIRSIGIR-2013-RaiberK #clustering #documentation #random #ranking #using
Ranking document clusters using markov random fields (FR, OK), pp. 333–342.
CASECASE-2013-BouhnikA #adaptation #correlation #exponential
Markov G/G/s model adaptation to factory operational curve though exponential correlation (SB, SA), pp. 730–734.
CASECASE-2013-ShaoLW #approach
A Markov chain approach to study flow disruptions on surgery in emergency care (XS, JL, DAW), pp. 990–995.
CASECASE-2013-XieLSD #analysis #approach #modelling #process
Modeling and analysis of hospital inpatient rescue process: A Markov chain approach (XX, JL, CHS, YD), pp. 978–983.
FoSSaCSFoSSaCS-2013-UmmelsB #modelling
Computing Quantiles in Markov Reward Models (MU, CB), pp. 353–368.
TACASTACAS-2013-BenediktLW #ltl #model checking
LTL Model Checking of Interval Markov Chains (MB, RL, JW), pp. 32–46.
CAVCAV-2013-ChatterjeeL #algorithm #performance #process
Faster Algorithms for Markov Decision Processes with Low Treewidth (KC, JL), pp. 543–558.
CSLCSL-2013-ChatterjeeCT #decidability #process #what
What is Decidable about Partially Observable Markov Decision Processes with ω-Regular Objectives (KC, MC, MT), pp. 165–180.
LICSLICS-2013-BrazdilCFK #performance #process
Trading Performance for Stability in Markov Decision Processes (TB, KC, VF, AK), pp. 331–340.
LICSLICS-2013-KozenLMP #process
Stone Duality for Markov Processes (DK, KGL, RM, PP), pp. 321–330.
VMCAIVMCAI-2013-DehnertKP #bisimulation #modelling #smt
SMT-Based Bisimulation Minimisation of Markov Models (CD, JPK, DP), pp. 28–47.
ICALPICALP-v1-2012-EtessamiSY #algorithm #branch #equation #polynomial #probability #process
Polynomial Time Algorithms for Branching Markov Decision Processes and Probabilistic Min(Max) Polynomial Bellman Equations (KE, AS, MY), pp. 314–326.
ICALPICALP-v2-2012-BrazdilKNW #process #termination
Minimizing Expected Termination Time in One-Counter Markov Decision Processes (TB, AK, PN, DW), pp. 141–152.
ICALPICALP-v2-2012-Fu #game studies #metric #process
Computing Game Metrics on Markov Decision Processes (HF), pp. 227–238.
CAiSECAiSE-2012-ZawawyKMM #analysis #logic #network #using
Requirements-Driven Root Cause Analysis Using Markov Logic Networks (HZ, KK, JM, SM), pp. 350–365.
ICEISICEIS-J-2012-RibeiroFBKE #algorithm #approach #learning #process
Combining Learning Algorithms: An Approach to Markov Decision Processes (RR, FF, MACB, ALK, FE), pp. 172–188.
ICMLICML-2012-FujimakiH #modelling
Factorized Asymptotic Bayesian Hidden Markov Models (RF, KH), p. 157.
ICMLICML-2012-JanzaminA #composition #independence
High-Dimensional Covariance Decomposition into Sparse Markov and Independence Domains (MJ, AA), p. 60.
ICMLICML-2012-MoldovanA #process
Safe Exploration in Markov Decision Processes (TMM, PA), p. 188.
ICMLICML-2012-MysoreS #modelling #performance
Variational Inference in Non-negative Factorial Hidden Markov Models for Efficient Audio Source Separation (GJM, MS), p. 194.
ICPRICPR-2012-AntoniukFH #learning #network
Learning Markov Networks by Analytic Center Cutting Plane Method (KA, VF, VH), pp. 2250–2253.
ICPRICPR-2012-AttamimiNN #multi #recognition #using
Hierarchical multilevel object recognition using Markov model (MA, TN, TN), pp. 2963–2966.
ICPRICPR-2012-GlodekSPS #classification #multi #network #using
Multi-modal Fusion based on classifiers using reject options and Markov Fusion Networks (MG, MS, GP, FS), pp. 1084–1087.
ICPRICPR-2012-HaindlRH
Potts compound Markovian texture model (MH, VR, VH), pp. 29–32.
ICPRICPR-2012-RaymondMOH #network
Map matching with Hidden Markov Model on sampled road network (RR, TM, TO, NH), pp. 2242–2245.
ICPRICPR-2012-SuLT #documentation #framework #image #learning #random #using
A learning framework for degraded document image binarization using Markov Random Field (BS, SL, CLT), pp. 3200–3203.
ICPRICPR-2012-UchidaFOF
Non-Markovian dynamic time warping (SU, MF, KO, YF), pp. 2294–2297.
SIGIRSIGIR-2012-LiDZ #query
A generalized hidden Markov model with discriminative training for query spelling correction (YL, HD, CZ), pp. 611–620.
QAPLQAPL-2012-Bernardo #bisimulation #concurrent #process
Weak Markovian Bisimulation Congruences and Exact CTMC-Level Aggregations for Concurrent Processes (MB), pp. 122–136.
SACSAC-2012-LassaigneP #approximate #process #scalability #verification
Approximate planning and verification for large markov decision processes (RL, SP), pp. 1314–1319.
SACSAC-2012-SchluterC #correlation #detection #modelling #predict #using
Hidden markov model-based time series prediction using motifs for detecting inter-time-serial correlations (TS, SC), pp. 158–164.
SACSAC-2012-SwainCNB #analysis #performance #using
Performance analysis of IEEE 802.11 IBSS power save mode using a discrete-time markov model (PS, SC, SN, PB), pp. 631–633.
SACSAC-2012-TrabelsiMY #folksonomy #modelling #named #recommendation
HMM-CARe: Hidden Markov Models for context-aware tag recommendation in folksonomies (CT, BM, SBY), pp. 957–961.
CASECASE-2012-WuY #estimation #linear #metric #using
State estimation for Markovian Jump Linear System using quantized measurements (HW, HY), pp. 527–531.
DACDAC-2012-PaekMSSK #named #random
PowerField: a transient temperature-to-power technique based on Markov random field theory (SP, SHM, WS, JS, LSK), pp. 630–635.
HPCAHPCA-2012-SuhAD #multi #named #reliability
MACAU: A Markov model for reliability evaluations of caches under Single-bit and Multi-bit Upsets (JS, MA, MD), pp. 3–14.
PDPPDP-2012-BaumannS #analysis #modelling #network #security
Markovian Modeling and Security Measure Analysis for Networks under Flooding DoS Attacks (HB, WS), pp. 298–302.
TACASTACAS-2012-WimmerJABK #modelling
Minimal Critical Subsystems for Discrete-Time Markov Models (RW, NJ, , BB, JPK), pp. 299–314.
CAVCAV-2012-GuetGHMS #search-based
Delayed Continuous-Time Markov Chains for Genetic Regulatory Circuits (CCG, AG, TAH, MM, AS), pp. 294–309.
LICSLICS-2012-AgrawalAGT #approximate #verification
Approximate Verification of the Symbolic Dynamics of Markov Chains (MA, SA, BG, PST), pp. 55–64.
ICDARICDAR-2011-CaoPN11a #identification #modelling #recognition #using
Handwritten and Typewritten Text Identification and Recognition Using Hidden Markov Models (HC, RP, PN), pp. 744–748.
ICDARICDAR-2011-JiangDLW #algorithm #novel #segmentation #string #using
A Novel Short Merged Off-line Handwritten Chinese Character String Segmentation Algorithm Using Hidden Markov Model (ZJ, XD, CL, YW), pp. 668–672.
VLDBVLDB-2011-NiuRDS #logic #named #network #scalability #statistics #using
Tuffy: Scaling up Statistical Inference in Markov Logic Networks using an RDBMS (FN, CR, AD, JWS), pp. 373–384.
CIAACIAA-2011-CarninoF #automaton #generative #random #using
Random Generation of Deterministic Acyclic Automata Using Markov Chains (VC, SDF), pp. 65–75.
ICALPICALP-v2-2011-CardelliLM #composition #logic
Modular Markovian Logic (LC, KGL, RM), pp. 380–391.
ICALPICALP-v2-2011-DengH #automaton #on the #semantics
On the Semantics of Markov Automata (YD, MH), pp. 307–318.
LATALATA-2011-DelahayeLLPW #problem
Decision Problems for Interval Markov Chains (BD, KGL, AL, MLP, AW), pp. 274–285.
AIIDEAIIDE-2011-HaRML #adaptation #game studies #logic #network #recognition
Goal Recognition with Markov Logic Networks for Player-Adaptive Games (EH, JPR, BWM, JCL).
CoGCIG-2011-UribeLSA #execution #game studies #process #trade-off
Discount and speed/execution tradeoffs in Markov Decision Process games (RU, FL, KS, CA), pp. 79–86.
CIKMCIKM-2011-ZhouH #framework #novel
A novel framework of training hidden markov support vector machines from lightly-annotated data (DZ, YH), pp. 2025–2028.
ICMLICML-2011-ChenDC #modelling #parametricity #topic
Topic Modeling with Nonparametric Markov Tree (HC, DBD, LC), pp. 377–384.
ICMLICML-2011-Gould #learning #linear #random
Max-margin Learning for Lower Linear Envelope Potentials in Binary Markov Random Fields (SG), pp. 193–200.
ICMLICML-2011-MannorT #optimisation #process
Mean-Variance Optimization in Markov Decision Processes (SM, JNT), pp. 177–184.
ICMLICML-2011-ThomasB #process
Conjugate Markov Decision Processes (PST, AGB), pp. 137–144.
KDDKDD-2011-SatpalBSRS #information management #logic #network #using #web
Web information extraction using markov logic networks (SS, SB, SS, RR, PS), pp. 1406–1414.
KDIRKDIR-2011-RenC #modelling #predict #transaction
Users Interest Prediction Model — Based on 2nd Markov Model and Inter-transaction Association Rules (YR, ALC), pp. 244–249.
QAPLQAPL-2011-AndreychenkoCW #infinity #modelling #on the fly
On-the-fly Uniformization of Time-Inhomogeneous Infinite Markov Population Models (AA, PC, VW), p. 1.
SACSAC-2011-HuangH #detection #multi #semantics
Semantic event detection in baseball videos based on a multi-output hidden Markov model (YFH, JJH), pp. 929–936.
SACSAC-2011-VenkateshGBC #fixpoint #implementation #modelling #recognition #speech #using
Fixed-point implementation of isolated sub-word level speech recognition using hidden Markov models (NV, RG, RB, MGC), pp. 368–373.
SACSAC-2011-WangXYC #web
Tagging web product titles based on hidden Markov model (PW, BX, YY, LC), pp. 43–48.
DATEDATE-2011-WelpK #approach #process #synthesis
An approach for dynamic selection of synthesis transformations based on Markov Decision Processes (TW, AK), pp. 1533–1536.
CAVCAV-2011-AndreychenkoMSW #identification #modelling #parametricity
Parameter Identification for Markov Models of Biochemical Reactions (AA, LM, DS, VW), pp. 83–98.
CAVCAV-2011-ChatterjeeHJS #algorithm #analysis #automaton #process
Symbolic Algorithms for Qualitative Analysis of Markov Decision Processes with Büchi Objectives (KC, MH, MJ, NS), pp. 260–276.
CSLCSL-2011-CardelliLM #axiom #logic #metric
Continuous Markovian Logic — From Complete Axiomatization to the Metric Space of Formulas (LC, KGL, RM), pp. 144–158.
LICSLICS-2011-BrazdilBCFK #multi #process
Two Views on Multiple Mean-Payoff Objectives in Markov Decision Processes (TB, VB, KC, VF, AK), pp. 33–42.
PODSPODS-2010-DeutchKM #fixpoint #on the #probability #query
On probabilistic fixpoint and Markov chain query languages (DD, CK, TM), pp. 215–226.
PODSPODS-2010-KimelfeldR #sequence
Transducing Markov sequences (BK, CR), pp. 15–26.
VLDBVLDB-2010-BenediktKOS #probability #xml
Probabilistic XML via Markov Chains (MB, EK, DO, PS), pp. 770–781.
EDMEDM-2010-BoyerPHWVL #modelling #tutorial
A Preliminary Investigation of Hierarchical Hidden Markov Models for Tutorial Planning (KEB, RP, EH, MDW, MAV, JCL), pp. 285–286.
EDMEDM-2010-JeongBJH #analysis #behaviour #effectiveness #learning #modelling #using
Analysis of Productive Learning Behaviors in a Structured Inquiry Cycle Using Hidden Markov Models (HJ, GB, JJ, LH), pp. 81–90.
CoGCIG-2010-BeaudryBCK #challenge #game studies #using
Using Markov decision theory to provide a fair challenge in a roll-and-move board game (EB, FB, SC, FK), pp. 1–8.
CIKMCIKM-2010-LangMWL #concept #random #using
Improved latent concept expansion using hierarchical markov random fields (HL, DM, BW, JTL), pp. 249–258.
ICMLICML-2010-DavisD #bottom-up #learning #network
Bottom-Up Learning of Markov Network Structure (JD, PMD), pp. 271–278.
ICMLICML-2010-KokD #learning #logic #network #using
Learning Markov Logic Networks Using Structural Motifs (SK, PMD), pp. 551–558.
ICMLICML-2010-PetrikTPZ #approximate #feature model #linear #process #source code #using
Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes (MP, GT, RP, SZ), pp. 871–878.
ICMLICML-2010-SongSGS #modelling
Hilbert Space Embeddings of Hidden Markov Models (LS, BB, SMS, GJG, AJS), pp. 991–998.
ICPRICPR-2010-CaoZL #random #using
Human Body Parts Tracking Using Sequential Markov Random Fields (XQC, JZ, ZQL), pp. 1759–1762.
ICPRICPR-2010-KimL #monte carlo #optimisation #random #using
Continuous Markov Random Field Optimization Using Fusion Move Driven Markov Chain Monte Carlo Technique (WK, KML), pp. 1364–1367.
ICPRICPR-2010-LeeCL #algorithm #data-driven #graph #monte carlo #using
A Graph Matching Algorithm Using Data-Driven Markov Chain Monte Carlo Sampling (JL, MC, KML), pp. 2816–2819.
ICPRICPR-2010-LiuLLLS #detection #modelling #process
Noise-Robust Voice Activity Detector Based on Hidden Semi-Markov Models (XL, YL, YL, HL, BS), pp. 81–84.
ICPRICPR-2010-ParkKS #detection #modelling #recognition #using #visual notation
Visual Recognition of Types of Structural Corridor Landmarks Using Vanishing Points Detection and Hidden Markov Models (YP, SSK, IHS), pp. 3292–3295.
KDDKDD-2010-ZhuLX #feature model #incremental #learning #named #performance #random
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields (JZ, NL, EPX), pp. 303–312.
KDIRKDIR-2010-TsengPF #classification #using
The Typhoon Track Classification using Tri-plots and Markov Chain (JCHT, HKKP, CF), pp. 364–369.
KMISKMIS-2010-ZyglarskiB #keyword #natural language #network
Keywords Extraction — Selecting Keywords in Natural Language Texts with Markov Chains and Neural Networks (BZ, PB), pp. 315–321.
QAPLQAPL-2010-RabeS #game studies
Optimal Time-Abstract Schedulers for CTMDPs and Markov Games (MNR, SS), pp. 144–158.
SACSAC-2010-DrumondG #concept #logic #ontology #using
Extracting ontology concept hierarchies from text using Markov logic (LD, RG), pp. 1354–1358.
SACSAC-2010-MenorBBGP #classification #taxonomy #using
Virus DNA-fragment classification using taxonomic hidden Markov model profiles (MM, KB, MB, YG, GP), pp. 1567–1571.
CASECASE-2010-Hsu #bound #safety
Control of continuous-time Markov chains with safety upper bounds (SPH), pp. 990–993.
CASECASE-2010-Tobon-MejiaMZT
A mixture of Gaussians Hidden Markov Model for failure diagnostic and prognostic (DATM, KM, NZ, GT), pp. 338–343.
DATEDATE-2010-CaoN #protocol
High-fidelity markovian power model for protocols (JC, AN), pp. 267–270.
DATEDATE-2010-KanoriaMM #analysis #monte carlo #statistics #using
Statistical static timing analysis using Markov chain Monte Carlo (YK, SM, AM), pp. 813–818.
DATEDATE-2010-ZhangLL #approach #modelling #simulation #using #verification
An abstraction-guided simulation approach using Markov models for microprocessor verification (TZ, TL, XL), pp. 484–489.
HPDCHPDC-2010-KrampeLS #hybrid #parallel
A hybrid Markov chain model for workload on parallel computers (AK, JL, WS), pp. 589–596.
TACASTACAS-2010-ValmariF
Simple O(m logn) Time Markov Chain Lumping (AV, GF), pp. 38–52.
TACASTACAS-2010-ZhangN #interactive #model checking
Model Checking Interactive Markov Chains (LZ, MRN), pp. 53–68.
CAVCAV-2010-HahnHWZ #model checking #modelling #named #parametricity
PARAM: A Model Checker for Parametric Markov Models (EMH, HH, BW, LZ), pp. 660–664.
ICLPICLP-J-2010-ChristiansenHLP #modelling
Inference with constrained hidden Markov models in PRISM (HC, CTH, OTL, MP), pp. 449–464.
LICSLICS-2010-Herbelin #logic #principle
An Intuitionistic Logic that Proves Markov’s Principle (HH), pp. 50–56.
ICDARICDAR-2009-AhmadVK #recognition #using #word
Lexicon-Based Word Recognition Using Support Vector Machine and Hidden Markov Model (ARA, CVG, MK), pp. 161–165.
ICDARICDAR-2009-LeloreB #documentation #image #using
Document Image Binarisation Using Markov Field Model (TL, FB), pp. 551–555.
ICDARICDAR-2009-MaHS #case study #design #modelling #online #recognition
A Study of Feature Design for Online Handwritten Chinese Character Recognition Based on Continuous-Density Hidden Markov Models (LM, QH, YS), pp. 526–530.
ICDARICDAR-2009-PengSGSB #documentation #identification #random
Markov Random Field Based Text Identification from Annotated Machine Printed Documents (XP, SS, VG, RS, KB), pp. 431–435.
ICDARICDAR-2009-Silva #analysis #documentation #learning #modelling
Learning Rich Hidden Markov Models in Document Analysis: Table Location (ACeS), pp. 843–847.
VLDBVLDB-2009-LetchnerRBP
Lahar Demonstration: Warehousing Markovian Streams (JL, CR, MB, MP), pp. 1610–1613.
SIGITESIGITE-2009-PakC #assessment #modelling #risk management #using
Asset priority risk assessment using hidden markov models (CP, JC), pp. 65–73.
ICPCICPC-2009-LinsteadHLB #first-order #java #modelling
Capturing Java naming conventions with first-order Markov models (EL, LH, CVL, PB), pp. 313–314.
ICALPICALP-v2-2009-ChaputDPP #approximate #process
Approximating Markov Processes by Averaging (PC, VD, PP, GDP), pp. 127–138.
CIKMCIKM-2009-GaoLMWL #framework
A general markov framework for page importance computation (BG, TYL, ZM, TW, HL), pp. 1835–1838.
CIKMCIKM-2009-KhareA #empirical #interface #segmentation #using
An empirical study on using hidden markov model for search interface segmentation (RK, YA), pp. 17–26.
ICMLICML-2009-ChengSS #matrix #modelling
Matrix updates for perceptron training of continuous density hidden Markov models (CCC, FS, LKS), pp. 153–160.
ICMLICML-2009-ChoiCW #modelling #multi
Exploiting sparse Markov and covariance structure in multiresolution models (MJC, VC, ASW), pp. 177–184.
ICMLICML-2009-DavisD #higher-order #logic
Deep transfer via second-order Markov logic (JD, PMD), pp. 217–224.
ICMLICML-2009-DoA #modelling #scalability
Large margin training for hidden Markov models with partially observed states (TMTD, TA), pp. 265–272.
ICMLICML-2009-KokD #learning #logic #network
Learning Markov logic network structure via hypergraph lifting (SK, PMD), pp. 505–512.
ICMLICML-2009-ZhuX #network #on the
On primal and dual sparsity of Markov networks (JZ, EPX), pp. 1265–1272.
KDDKDD-2009-ZhuXZ #network
Primal sparse Max-margin Markov networks (JZ, EPX, BZ), pp. 1047–1056.
SIGIRSIGIR-2009-ItakuraC #detection #using #wiki
Using dynamic markov compression to detect vandalism in the wikipedia (KYI, CLAC), pp. 822–823.
SIGIRSIGIR-2009-Lease #query #random
An improved markov random field model for supporting verbose queries (ML), pp. 476–483.
QAPLQAPL-2009-Bernardo #logic #nondeterminism #probability #process #testing
Uniform Logical Characterizations of Testing Equivalences for Nondeterministic, Probabilistic and Markovian Processes (MB), pp. 3–23.
QAPLQAPL-2009-MuraPPR
Exploiting non-Markovian Bio-Processes (IM, DP, CP, AR), pp. 83–98.
CASECASE-2009-HariharanB #process #using
Misplaced item search in a warehouse using an RFID-based Partially Observable Markov Decision Process (POMDP) model (SH, STSB), pp. 443–448.
CASECASE-2009-SinghKP #fault #multi
A factorial hidden markov model (FHMM)-based reasoner for diagnosing multiple intermittent faults (SS, AK, KRP), pp. 146–151.
CASECASE-2009-VazquezS #modelling #performance #petri net
Performance control of Markovian Petri nets via fluid models: A stock-level control example (CRV, MS), pp. 30–36.
FoSSaCSFoSSaCS-2009-NeuhausserSK #nondeterminism #process
Delayed Nondeterminism in Continuous-Time Markov Decision Processes (MRN, MS, JPK), pp. 364–379.
CAVCAV-2009-HahnHWZ #infinity #model checking #named
INFAMY: An Infinite-State Markov Model Checker (EMH, HH, BW, LZ), pp. 641–647.
CAVCAV-2009-HenzingerMW #abstraction #infinity
Sliding Window Abstraction for Infinite Markov Chains (TAH, MM, VW), pp. 337–352.
CAVCAV-2009-KitchenK #constraints #integer #monte carlo
A Markov Chain Monte Carlo Sampler for Mixed Boolean/Integer Constraints (NK, AK), pp. 446–461.
LICSLICS-2009-ChenHKM #automaton #model checking #specification
Quantitative Model Checking of Continuous-Time Markov Chains Against Timed Automata Specifications (TC, TH, JPK, AM), pp. 309–318.
VMCAIVMCAI-2009-WimmerBB #bound #generative #model checking #using
Counterexample Generation for Discrete-Time Markov Chains Using Bounded Model Checking (RW, BB, BB), pp. 366–380.
JCDLJCDL-2008-Hetzner #metadata #modelling #using
A simple method for citation metadata extraction using hidden markov models (EH), pp. 280–284.
DLTDLT-J-2007-DoyenHR08 #equivalence
Equivalence of Labeled Markov Chains (LD, TAH, JFR), pp. 549–563.
ICALPICALP-B-2008-BrazdilFK #branch #process #synthesis #verification
Controller Synthesis and Verification for Markov Decision Processes with Qualitative Branching Time Objectives (TB, VF, AK), pp. 148–159.
CIKMCIKM-2008-Domingos #information management #logic
Markov logic: a unifying language for knowledge and information management (PMD), p. 519.
CIKMCIKM-2008-HuangS #query #using
A latent variable model for query expansion using the hidden markov model (QH, DS), pp. 1417–1418.
ICMLICML-2008-GaelSTG #infinity
Beam sampling for the infinite hidden Markov model (JVG, YS, YWT, ZG), pp. 1088–1095.
ICMLICML-2008-HuynhM #learning #logic #network #parametricity
Discriminative structure and parameter learning for Markov logic networks (TNH, RJM), pp. 416–423.
ICMLICML-2008-NarayanamurthyR #on the #process #symmetry
On the hardness of finding symmetries in Markov decision processes (SMN, BR), pp. 688–695.
ICMLICML-2008-SalakhutdinovM08a #matrix #monte carlo #probability #using
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo (RS, AM), pp. 880–887.
ICMLICML-2008-ZhuXZ #network
Laplace maximum margin Markov networks (JZ, EPX, BZ), pp. 1256–1263.
ICPRICPR-2008-Bouchaffra #modelling
Embedding HMM’s-based models in a Euclidean space: The topological hidden Markov models (DB), pp. 1–4.
ICPRICPR-2008-ChenHCZL #adaptation #detection #random
Change detection based on adaptive Markov Random Fields (KC, CH, JC, ZZ, HL), pp. 1–4.
ICPRICPR-2008-ElmezainAAM #gesture #modelling #recognition
A Hidden Markov Model-based continuous gesture recognition system for hand motion trajectory (ME, AAH, JA, BM), pp. 1–4.
ICPRICPR-2008-GuoYZZY #embedded #random #using
Face super-resolution using 8-connected Markov Random Fields with embedded prior (KG, XY, RZ, GZ, SY), pp. 1–4.
ICPRICPR-2008-KimuraPTYK #modelling #probability #random #visual notation
Dynamic Markov random fields for stochastic modeling of visual attention (AK, DP, TT, JY, KK), pp. 1–5.
ICPRICPR-2008-LevadaMT #image #modelling #on the #probability #random
On the asymptotic variances of Gaussian Markov Random Field model hyperparameters in stochastic image modeling (ALML, NDAM, AT), pp. 1–4.
ICPRICPR-2008-PrasadSKMN #modelling
Improvements in hidden Markov model based Arabic OCR (RP, SS, MK, RM, PN), pp. 1–4.
ICPRICPR-2008-SezerMAC #detection #named
NorMaL: Non-compact Markovian Likelihood for change detection (OGS, JLM, YA, DBC), pp. 1–4.
ICPRICPR-2008-VachaH #invariant #random
Illumination invariants based on Markov random fields (PV, MH), pp. 1–4.
ICPRICPR-2008-WangI #classification #image #modelling #multi #semantics
Combining multiple spatial hidden Markov models in image semantic classification and annotation (LW, HHSI), pp. 1–4.
ICPRICPR-2008-ZhuangZHH #estimation #using
Face age estimation using patch-based hidden Markov model supervectors (XZ, XZ, MHJ, TSH), pp. 1–4.
KDDKDD-2008-FujiwaraSY #identification #modelling #named #performance
SPIRAL: efficient and exact model identification for hidden Markov models (YF, YS, MY), pp. 247–255.
SACSAC-2008-MohseniMMS
A Farsi part-of-speech tagger based on Markov model (MM, HM, BMB, MSf), pp. 1588–1589.
CASECASE-2008-ZhuCS #recognition #using
Human intention recognition in Smart Assisted Living Systems using a Hierarchical Hidden Markov Model (CZ, QC, WS), pp. 253–258.
DATEDATE-2008-TanQ #framework #power management #probability #using
A Framework of Stochastic Power Management Using Hidden Markov Model (YT, QQ), pp. 92–97.
PDPPDP-2008-KiasariRSH #performance
A Markovian Performance Model for Networks-on-Chip (AEK, DR, HSA, SH), pp. 157–164.
FoSSaCSFoSSaCS-2008-ChatterjeeSH #model checking
Model-Checking ω-Regular Properties of Interval Markov Chains (KC, KS, TAH), pp. 302–317.
DocEngDocEng-2007-ZouLT #analysis #approach #html
Structure and content analysis for html medical articles: a hidden markov model approach (JZ, DXL, GRT), pp. 199–201.
ICDARICDAR-2007-BharathM #modelling #online #recognition #word
Hidden Markov Models for Online Handwritten Tamil Word Recognition (AB, SM), pp. 506–510.
ICDARICDAR-2007-LemaitreGP #2d #analysis #approach #layout
Preliminary experiments in layout analysis of handwritten letters based on textural and spatial information and a 2D Markovian approach (ML, EG, FJP), pp. 1023–1027.
ICDARICDAR-2007-LuthyVB #modelling #segmentation #using
Using Hidden Markov Models as a Tool for Handwritten Text Line Segmentation (FL, TV, HB), p. 8–?.
ICDARICDAR-2007-SilvaN #classification #modelling #performance #visualisation
A Visualization Tool to Improve the Performance of a Classifier Based on Hidden Markov Models (GdS, MN), pp. 1083–1087.
ICDARICDAR-2007-ToujAA07a #approach #hybrid #modelling #recognition
A hybrid approach for off-line Arabic handwriting recognition based on a Planar Hidden Markov modeling (SMT, NEBA, HA), pp. 964–968.
ICDARICDAR-2007-ZhouLQA #classification #random
Text/Non-text Ink Stroke Classification in Japanese Handwriting Based on Markov Random Fields (XDZ, CLL, SQ, ÉA), pp. 377–381.
SFMSFM-2007-Bernardo #behaviour #overview
A Survey of Markovian Behavioral Equivalences (MB), pp. 180–219.
SFMSFM-2007-Stewart #modelling #performance
Performance Modelling and Markov Chains (WJS), pp. 1–33.
CIKMCIKM-2007-CaoGNB #modelling #query
Extending query translation to cross-language query expansion with markov chain models (GC, JG, JYN, JB), pp. 351–360.
CIKMCIKM-2007-Metzler #automation #feature model #information retrieval #random
Automatic feature selection in the markov random field model for information retrieval (DM), pp. 253–262.
CIKMCIKM-2007-ZhouHZS
A segment-based hidden markov model for real-setting pinyin-to-chinese conversion (XZ, XH, XZ, XS), pp. 1027–1030.
ICMLICML-2007-Azran #algorithm #learning #multi #random
The rendezvous algorithm: multiclass semi-supervised learning with Markov random walks (AA), pp. 49–56.
ICMLICML-2007-DelageM #nondeterminism #optimisation #performance #process
Percentile optimization in uncertain Markov decision processes with application to efficient exploration (ED, SM), pp. 225–232.
ICMLICML-2007-MihalkovaM #bottom-up #learning #logic #network
Bottom-up learning of Markov logic network structure (LM, RJM), pp. 625–632.
ICMLICML-2007-ZhuNZW #random #web
Dynamic hierarchical Markov random fields and their application to web data extraction (JZ, ZN, BZ, JRW), pp. 1175–1182.
MLDMMLDM-2007-AriuGP #modelling #network
Sensing Attacks in Computers Networks with Hidden Markov Models (DA, GG, RP), pp. 449–463.
SIGIRSIGIR-2007-MetzlerC #concept #random #using
Latent concept expansion using markov random fields (DM, WBC), pp. 311–318.
SACSAC-2007-MilsztajnG #3d #algorithm #random #search-based #segmentation #using
Three-dimensional segmentation of brain tissues using Markov random fields and genetic algorithms (FM, KdG), pp. 745–746.
CASECASE-2007-NarasimhaKS #approach #email #information management #process
A Semi Markov Decision Process Approach To E-mail Management In A Knowledge Work Environment (CYN, MK, RS), pp. 1051–1056.
TACASTACAS-2007-Derisavi #algorithm
A Symbolic Algorithm for Optimal Markov Chain Lumping (SD), pp. 139–154.
TACASTACAS-2007-EtessamiKVY #model checking #multi #process
Multi-objective Model Checking of Markov Decision Processes (KE, MZK, MYV, MY), pp. 50–65.
CAVCAV-2007-AlfaroR #abstraction #process
Magnifying-Lens Abstraction for Markov Decision Processes (LdA, PR), pp. 325–338.
CAVCAV-2007-KatoenKLW #abstraction
Three-Valued Abstraction for Continuous-Time Markov Chains (JPK, DK, ML, VW), pp. 311–324.
LICSLICS-2007-GimbertZ #multi #process
Limits of Multi-Discounted Markov Decision Processes (HG, WZ), pp. 89–98.
CIKMCIKM-2006-CaoNB #documentation #modelling #query
Constructing better document and query models with markov chains (GC, JYN, JB), pp. 800–801.
ICMLICML-2006-DegrisSW #learning #problem #process
Learning the structure of Factored Markov Decision Processes in reinforcement learning problems (TD, OS, PHW), pp. 257–264.
ICMLICML-2006-LiLC #process
Region-based value iteration for partially observable Markov decision processes (HL, XL, LC), pp. 561–568.
ICMLICML-2006-MaggioniM #analysis #evaluation #multi #performance #policy #process #using
Fast direct policy evaluation using multiscale analysis of Markov diffusion processes (MM, SM), pp. 601–608.
ICMLICML-2006-NarasimhanVS #constraints #latency #modelling #online
Online decoding of Markov models under latency constraints (MN, PAV, MS), pp. 657–664.
ICMLICML-2006-RavikumarL #estimation #metric #polynomial #programming #random
Quadratic programming relaxations for metric labeling and Markov random field MAP estimation (PDR, JDL), pp. 737–744.
ICMLICML-2006-SenG #learning #network
Cost-sensitive learning with conditional Markov networks (PS, LG), pp. 801–808.
ICMLICML-2006-ToussaintS #probability #process
Probabilistic inference for solving discrete and continuous state Markov Decision Processes (MT, AJS), pp. 945–952.
ICPRICPR-v1-2006-AndradeBF06a #analysis #modelling
Hidden Markov Models for Optical Flow Analysis in Crowds (ELA, SB, RBF), pp. 460–463.
ICPRICPR-v1-2006-CarterYF #approach #behaviour #recognition
A Combined Bayesian Markovian Approach for Behaviour Recognition (NLC, DPY, JMF), pp. 761–764.
ICPRICPR-v1-2006-DemonceauxV #adaptation #random
Adaptative Markov Random Fields for Omnidirectional Vision (CD, PV), pp. 848–851.
ICPRICPR-v1-2006-WenGL #clustering #detection #monte carlo
Markov Chain Monte Carlo Data Association for Merge and Split Detection in Tracking Protein Clusters (QW, JG, KLP), pp. 1030–1033.
ICPRICPR-v1-2006-XieL #animation #modelling #speech #using
Speech Animation Using Coupled Hidden Markov Models (LX, ZQL), pp. 1128–1131.
ICPRICPR-v1-2006-ZengL #random #segmentation #using
Stroke Segmentation of Chinese Characters Using Markov Random Fields (JZ, ZQL), pp. 868–871.
ICPRICPR-v1-2006-ZengL06a #fuzzy #random #recognition
Type-2 Fuzzy Markov Random Fields to Handwritten Character Recognition (JZ, ZQL), pp. 1162–65.
ICPRICPR-v2-2006-YangLWW #clustering #robust
Robust Clustering based on Winner-Population Markov Chain (FWY, HJL, PSPW, HHW), pp. 589–592.
ICPRICPR-v2-2006-YuCMW #detection #monte carlo #multi
Boosted Markov Chain Monte Carlo Data Association for Multiple Target Detection and Tracking (QY, IC, GGM, BW), pp. 675–678.
ICPRICPR-v3-2006-BouchaffraT #recognition #using
Protein Fold Recognition using a Structural Hidden Markov Model (DB, JT), pp. 186–189.
ICPRICPR-v3-2006-DuongPBV #behaviour #exponential #modelling #product line #recognition
Human Behavior Recognition with Generic Exponential Family Duration Modeling in the Hidden Semi-Markov Model (TVD, DQP, HHB, SV), pp. 202–207.
ICPRICPR-v3-2006-NicolasPH #approach #documentation #segmentation
A Markovian Approach for Handwritten Document Segmentation (SN, TP, LH), pp. 292–295.
ICPRICPR-v3-2006-SandersonG #kernel #on the #sequence
On Authorship Attribution via Markov Chains and Sequence Kernels (CS, SG), pp. 437–440.
ICPRICPR-v3-2006-ZhongW #detection #random
Object Detection Based on Combination of Conditional Random Field and Markov Random Field (PZ, RW), pp. 160–163.
QAPLQAPL-2005-WolfBM06
Trace Machines for Observing Continuous-Time Markov Chains (VW, CB, MEMC), pp. 259–277.
DATEDATE-2006-RongP #algorithm #formal method #online #process
Determining the optimal timeout values for a power-managed system based on the theory of Markovian processes: offline and online algorithms (PR, MP), pp. 1128–1133.
TACASTACAS-2006-SenVA #model checking #nondeterminism
Model-Checking Markov Chains in the Presence of Uncertainties (KS, MV, GA), pp. 394–410.
DRRDRR-2005-TaghvaCPN #modelling #using
Address extraction using hidden Markov models (KT, JSC, RP, TAN), pp. 119–126.
ICDARICDAR-2005-El-HajjLM #modelling #recognition #using
Arabic Handwriting Recognition Using Baseline Dependant Features and Hidden Markov Modeling (REH, LLS, CM), pp. 893–897.
ICDARICDAR-2005-FuDLJ #algorithm #modelling #recognition #segmentation #string
A Hidden Markov Model Based Segmentation and Recognition Algorithm for Chinese Handwritten Address Character Strings (QF, XQD, CSL, YJ), pp. 590–594.
ICDARICDAR-2005-NelPH #modelling #multi #using
Estimating the Pen Trajectories of Multi-Path Static Scripts Using Hidden Markov Models (EMN, JAdP, BMH), pp. 41–47.
ICDARICDAR-2005-NicolasKPH #documentation #random #segmentation #using
Handwritten Document Segmentation Using Hidden Markov Random Fields (SN, YK, TP, LH), pp. 212–216.
ICDARICDAR-2005-ZengL #random #recognition
Markov Random Fields for Handwritten Chinese Character Recognition (JZ, ZQL), pp. 101–105.
ICALPICALP-2005-EtessamiY #game studies #probability #process #recursion
Recursive Markov Decision Processes and Recursive Stochastic Games (KE, MY), pp. 891–903.
AIIDEAIIDE-2005-ZubekH #interactive #modelling #parallel
Hierarchical Parallel Markov Models of Interaction (RZ, IH), pp. 141–146.
CIKMCIKM-2005-JiangZ #modelling #using
Accurately extracting coherent relevant passages using hidden Markov models (JJ, CZ), pp. 289–290.
ICMLICML-2005-AndersonM #algorithm #learning #modelling
Active learning for Hidden Markov Models: objective functions and algorithms (BA, AM), pp. 9–16.
ICMLICML-2005-KokD #learning #logic #network
Learning the structure of Markov logic networks (SK, PMD), pp. 441–448.
ICMLICML-2005-RohanimaneshM #approach #concurrent #generative #named #process
Coarticulation: an approach for generating concurrent plans in Markov decision processes (KR, SM), pp. 720–727.
ICMLICML-2005-WangWGSC #modelling #random #semantics
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields (SW, SW, RG, DS, LC), pp. 948–955.
KDDKDD-2005-BesemannD #integration #mining
Integration of profile hidden Markov model output into association rule mining (CB, AD), pp. 538–543.
SEKESEKE-2005-SongLN #evaluation #framework #named #object-oriented #specification
OOMSE — An Object Oriented Markov Chain Specification and Evaluation Framework (HS, CL, RN), pp. 229–234.
SIGIRSIGIR-2005-GhoshalIK #automation #image #modelling #retrieval #video
Hidden Markov models for automatic annotation and content-based retrieval of images and video (AG, PI, SK), pp. 544–551.
SIGIRSIGIR-2005-MetzlerC #dependence #random
A Markov random field model for term dependencies (DM, WBC), pp. 472–479.
SACSAC-2005-WanMA #array #random #similarity #using
Cleaning microarray expression data using Markov random fields based on profile similarity (RW, HM, KFA), pp. 206–207.
DATEDATE-2005-FahmyCL #detection #hardware
Hardware Acceleration of Hidden Markov Model Decoding for Person Detection (SAF, PYKC, WL), pp. 8–13.
STOCSTOC-2005-MosselR #learning #modelling
Learning nonsingular phylogenies and hidden Markov models (EM, SR), pp. 366–375.
TACASTACAS-2005-RemkeHC #infinity #model checking
Model Checking Infinite-State Markov Chains (AR, BRH, LC), pp. 237–252.
LICSLICS-2005-AbdullaHM #finite #infinity #verification
Verifying Infinite Markov Chains with a Finite Attractor or the Global Coarseness Property (PAA, NBH, RM), pp. 127–136.
TPDLECDL-2004-OkadaTA #component #modelling #using
Bibliographic Component Extraction Using Support Vector Machines and Hidden Markov Models (TO, AT, JA), pp. 501–512.
ICMLICML-2004-TaskarCK #learning #network
Learning associative Markov networks (BT, VC, DK).
ICMLICML-2004-WellingRT #approximate
Approximate inference by Markov chains on union spaces (MW, MRZ, YWT).
ICMLICML-2004-WierstraW #modelling
Utile distinction hidden Markov models (DW, MW).
ICPRICPR-v1-2004-ClausiY #comparison #random #segmentation #using
Texture Segmentation Comparison Using Grey Level Co-Occurrence Probabilities and Markov Random Fields (DAC, BY), pp. 584–587.
ICPRICPR-v1-2004-CoskerMRH #animation #speech #using
Speech Driven Facial Animation using a Hidden Markov Coarticulation Model (DC, ADM, PLR, YH), pp. 128–131.
ICPRICPR-v1-2004-LeL #image #modelling #using
Recognizing Frontal Face Images Using Hidden Markov Models with One Training Image per Person (HSL, HL), pp. 318–321.
ICPRICPR-v1-2004-SunG #image #random #segmentation
Bayesian Image Segmentation Based on an Inhomogeneous Hidden Markov Random Field (JS, DG), pp. 596–599.
ICPRICPR-v1-2004-ZengL #fuzzy #modelling #recognition
Type-2 Fuzzy Hidden Markov Models to Phoneme Recognition (JZ, ZQL), pp. 192–195.
ICPRICPR-v2-2004-DupreA #modelling #recognition
Hidden Markov Models for Couples of Letters Applied to Handwriting Recognition (XD, EA), pp. 618–621.
ICPRICPR-v2-2004-GaoHBW #analysis #process #using
Dining Activity Analysis Using a Hidden Markov Model (JG, AGH, AB, HDW), pp. 915–918.
ICPRICPR-v3-2004-AntoniolC #approach #array #image #random
A Markov Random Field Approach to Microarray Image Gridding (GA, MC), pp. 550–553.
ICPRICPR-v3-2004-BagciAKC #eye tracking #modelling #using
Eye Tracking Using Markov Models (AMB, RA, AAK, EC), pp. 818–821.
ICPRICPR-v3-2004-HuangMP #hybrid #random #recognition #using
A Hybrid Face Recognition Method using Markov Random Fields (RH, DNM, VP), pp. 157–160.
ICPRICPR-v3-2004-JiaQD #detection #modelling #online
An Advanced Segmental Semi-Markov Model Based Online Series Pattern Detection (SJ, YQ, GD), pp. 634–637.
ICPRICPR-v3-2004-MatsuiCUM #monte carlo #recognition #using
Bayesian Face Recognition using a Markov Chain Monte Carlo Method (AM, SC, FU, TM), pp. 918–921.
ICPRICPR-v3-2004-NovakLCMAHA #analysis #modelling #using
Morphology Analysis of Physiological Signals Using Hidden Markov Models (DN, LL, DCF, PM, TAA, YH, MA), pp. 754–757.
ICPRICPR-v4-2004-MurakitaII #monte carlo #using
Human Tracking using Floor Sensors based on the Markov Chain Monte Carlo Method (TM, TI, HI), pp. 917–920.
KDDKDD-2004-CohenS #integration #process
Exploiting dictionaries in named entity extraction: combining semi-Markov extraction processes and data integration methods (WWC, SS), pp. 89–98.
SIGIRSIGIR-2004-HoenkampS #documentation
The document as an ergodic markov chain (EH, DS), pp. 496–497.
FoSSaCSFoSSaCS-2004-MisloveOPW #process
Duality for Labelled Markov Processes (MWM, JO, DP, JW), pp. 393–407.
TACASTACAS-2004-BaierHHK #bound #performance #process #reachability
Efficient Computation of Time-Bounded Reachability Probabilities in Uniform Continuous-Time Markov Decision Processes (CB, BRH, HH, JPK), pp. 61–76.
CAVCAV-2004-BustanRV #verification
Verifying ω-Regular Properties of Markov Chains (DB, SR, MYV), pp. 189–201.
DRRDRR-2003-Pham #modelling #recognition #statistics
Applications of geostatistics and Markov models for logo recognition (TDP), pp. 20–27.
ICDARICDAR-2003-ChoisyB #network #recognition #word
Coupling of a local vision by Markov field and a global vision by Neural Network for the recognition of handwritten words (CC, AB), pp. 849–853.
ICDARICDAR-2003-PerroneV #documentation #retrieval
Markov Model Document Retrieval (MPP, AV), pp. 1223–1227.
ICDARICDAR-2003-ShafieiR #algorithm #modelling #online #segmentation #using #verification
A New On-Line Signature Verification Algorithm Using Variable Length Segmentation and Hidden Markov Models (MMS, HRR), p. 443–?.
ICDARICDAR-2003-YamazakiNK #modelling #using #verification
Text-indicated Writer Verification Using Hidden Markov Models (YY, TN, NK), pp. 329–332.
ICDARICDAR-2003-ZhengLD03a #documentation #identification #image #random #using
Text Identification in Noisy Document Images Using Markov Random Field (YZ, HL, DSD), p. 599–?.
ICEISICEIS-v2-2003-BouchaffraT #industrial
Structural Hidden Markov Model and Its Application in Automotive Industry (DB, JT), pp. 155–164.
ICEISICEIS-v2-2003-ChadesSC #multi #process #using
Planning Cooperative Homogeneous Multiagent Systems Using Markov Decision Processes (IC, BS, FC), pp. 426–429.
CIKMCIKM-2003-MelucciO #generative #modelling #novel
A novel method for stemmer generation based on hidden markov models (MM, NO), pp. 131–138.
ICMLICML-2003-AltunTH
Hidden Markov Support Vector Machines (YA, IT, TH), pp. 3–10.
ICMLICML-2003-Duff03a #approximate
Diffusion Approximation for Bayesian Markov Chains (MOD), pp. 139–146.
KDDKDD-2003-TsamardinosAS #performance
Time and sample efficient discovery of Markov blankets and direct causal relations (IT, CFA, ARS), pp. 673–678.
MLDMMLDM-2003-BicegoMF #clustering #modelling #sequence #similarity #using
Similarity-Based Clustering of Sequences Using Hidden Markov Models (MB, VM, MATF), pp. 86–95.
SASSAS-2003-Monniaux #abstract interpretation #process #source code
Abstract Interpretation of Programs as Markov Decision Processes (DM), pp. 237–254.
SACSAC-2003-KatzerKS #array #random
A Markov Random Field Model of Microarray Gridding (MK, FK, GS), pp. 72–77.
DACDAC-2003-LiYRP #generative #using
A scan BIST generation method using a markov source and partial bit-fixing (WL, CY, SMR, IP), pp. 554–559.
DACDAC-2003-RongP #approach #mobile #network
Extending the lifetime of a network of battery-powered mobile devices by remote processing: a markovian decision-based approach (PR, MP), pp. 906–911.
DATEDATE-2003-PolianBR #optimisation #pseudo #random
Evolutionary Optimization of Markov Sources for Pseudo Random Scan BIST (IP, BB, SMR), pp. 11184–11185.
LICSLICS-2003-DanosD #approximate #performance #process
Labelled Markov Processes: Stronger and Faster Approximations (VD, JD), pp. 341–350.
HTHT-2002-ZhuHH #modelling #predict #using #web
Using Markov models for web site link prediction (JZ, JH, JGH), pp. 169–170.
VLDBVLDB-2002-LimWPVP #estimation #named #online #self #xml
XPathLearner: An On-line Self-Tuning Markov Histogram for XML Path Selectivity Estimation (LL, MW, SP, JSV, RP), pp. 442–453.
ICALPICALP-2002-BreugelSW #process #testing
Testing Labelled Markov Processes (FvB, SS, JW), pp. 537–548.
ICALPICALP-2002-Hertling
A Banach-Mazur Computable But Not Markov Computable Function on the Computable Real Numbers (PH), pp. 962–972.
ICMLICML-2002-Bonet #algorithm #process
An epsilon-Optimal Grid-Based Algorithm for Partially Observable Markov Decision Processes (BB), pp. 51–58.
ICMLICML-2002-KakadeTR
An Alternate Objective Function for Markovian Fields (SK, YWT, STR), pp. 275–282.
ICMLICML-2002-OliverG #modelling #named
MMIHMM: Maximum Mutual Information Hidden Markov Models (NO, AG), pp. 466–473.
ICMLICML-2002-SlonimBFT #feature model #memory management #multi
Discriminative Feature Selection via Multiclass Variable Memory Markov Model (NS, GB, SF, NT), pp. 578–585.
ICMLICML-2002-StrensBE #monte carlo #optimisation #using
Markov Chain Monte Carlo Sampling using Direct Search Optimization (MJAS, MB, NE), pp. 602–609.
ICMLICML-2002-ThamDR #classification #learning #monte carlo #using
Sparse Bayesian Learning for Regression and Classification using Markov Chain Monte Carlo (SST, AD, KR), pp. 634–641.
ICPRICPR-v1-2002-ChengCO #image
A Trainable Hierarchical Hidden Markov Tree Model for Color Image Annotation (LC, TC, VO), pp. 192–195.
ICPRICPR-v1-2002-Meas-YedidTO #analysis #clustering #image #random #segmentation
Color Image Segmentation Based on Markov Random Field Clustering for Histological Image Analysis (VMY, ST, JCOM), pp. 796–799.
ICPRICPR-v1-2002-TakizawaYMTIM #3d #image #modelling #random #recognition #using
Recognition of Lung Nodules from X-ray CT Images Using 3D Markov Random Field Models (HT, SY, TM, YT, TI, MM), pp. 99–102.
ICPRICPR-v2-2002-DavisLC #estimation #multi #parametricity #sequence
Improved Estimation of Hidden Markov Model Parameters from Multiple Observation Sequences (RIAD, BCL, TC), pp. 168–171.
ICPRICPR-v2-2002-KamijoIS #image #invariant #random #segmentation
Illumination Invariant Segmentation of Spatio-Temporal Images by Spatio-Temporal Markov Random Field Model (SK, KI, MS), pp. 617–622.
ICPRICPR-v2-2002-MullerWHR #3d #modelling #pseudo #recognition #using
Facial Expression Recognition Using Pseudo 3-D Hidden Markov Models (SM, FW, FH, GR), pp. 32–35.
ICPRICPR-v2-2002-RiviereMMTPF #graph #learning #random #relational #using
Relational Graph Labelling Using Learning Techniques and Markov Random Fields (DR, JFM, JMM, FT, DPO, VF), pp. 172–175.
ICPRICPR-v2-2002-SanchezBK #video
Coupled Markov Chains for Video Contents Characterization (JMS, XB, JRK), pp. 461–464.
ICPRICPR-v2-2002-SatoK #gesture #modelling #multi #recognition
Extension of Hidden Markov Models to Deal with Multiple Candidates of Observations and its Application to Mobile-Robot-Oriented Gesture Recognition (YS, TK), p. 515–?.
ICPRICPR-v2-2002-YeL #image #modelling #segmentation #using
Wavelet-Based Unsupervised SAR Image Segmentation Using Hidden Markov Tree Models (ZY, CCL), pp. 729–732.
ICPRICPR-v3-2002-Al-MaadeedHE #approach #recognition #using #word
Recognition of Off-Line Handwritten Arabic Words Using Hidden Markov Model Approach (SAM, CH, DE), pp. 481–484.
ICPRICPR-v3-2002-BaesensECV #classification #learning #monte carlo #network #using
Learning Bayesian Network Classifiers for Credit Scoring Using Markov Chain Monte Carlo Search (BB, MEP, RC, JV), pp. 49–52.
ICPRICPR-v3-2002-CaputoBN #random #recognition #robust #using
Robust Appearance-Based Object Recognition Using a Fully Connected Markov Random Field (BC, SB, HN), pp. 565–568.
ICPRICPR-v3-2002-FengDW #modelling #recognition #using
Chinese Handwriting Recognition Using Hidden Markov Models (BF, XD, YW), pp. 212–215.
ICPRICPR-v3-2002-HallouliLS #case study #comparative #data fusion #recognition
A Comparative Study between Decision Fusion and Data Fusion in Markovian Printed Character Recognition (KH, LLS, MS), pp. 147–150.
ICPRICPR-v3-2002-VinciarelliB #modelling #recognition #using #word
Offline Cursive Word Recognition using Continuous Density Hidden Markov Models Trained with PCA or ICA Features (AV, SB), pp. 81–84.
ICPRICPR-v3-2002-WolfD #quality #random #using
Binarization of Low Quality Text Using a Markov Random Field Model (CW, DSD), pp. 160–163.
ICPRICPR-v4-2002-ChenOB #random #recognition #segmentation
Text Segmentation and Recognition in Complex Background Based on Markov Random Field (DC, JMO, HB), pp. 227–230.
ICPRICPR-v4-2002-DassJL #detection #modelling #random #synthesis #using
Face Detection and Synthesis Using Markov Random Field Models (SCD, AKJ, XL), pp. 201–204.
KDDKDD-2002-AndersonDW #adaptation #modelling #navigation #relational #web
Relational Markov models and their application to adaptive web navigation (CRA, PMD, DSW), pp. 143–152.
KDDKDD-2002-ChudovaS #sequence
Pattern discovery in sequences under a Markov assumption (DC, PS), pp. 153–162.
ICDARICDAR-2001-GrandidierSGS #modelling #power of
An a priori Indicator of the Discrimination Power of Discrete Hidden Markov Models (FG, RS, MG, CYS), pp. 350–355.
ICDARICDAR-2001-GuoM #modelling #using
Separating Handwritten Material from Machine Printed Text Using Hidden Markov Models (JKG, MYM), pp. 439–443.
ICDARICDAR-2001-LeedhamTY #identification #using
Handwritten Country Name Identification Using Vector Quantisation and Hidden Markov Model (GL, WKT, WLY), pp. 685–688.
ICDARICDAR-2001-MiledA #modelling #recognition
Planar Markov Modeling for Arabic Writing Recognition: Advancement State (HM, NEBA), pp. 69–73.
ICDARICDAR-2001-NatarajanESM #modelling #using
Videotext OCR Using Hidden Markov Models (PN, BE, RMS, JM), pp. 947–951.
ICDARICDAR-2001-SerraduraSV #classification #modelling #using #web
Web Sites Thematic Classification Using Hidden Markov Models (LS, MS, NV), pp. 1094–1099.
ICMLICML-2001-EngelM #embedded #learning #process
Learning Embedded Maps of Markov Processes (YE, SM), pp. 138–145.
ICMLICML-2001-SatoK #learning #problem
Average-Reward Reinforcement Learning for Variance Penalized Markov Decision Problems (MS, SK), pp. 473–480.
ICMLICML-2001-SeldinBT #memory management #segmentation #sequence
Unsupervised Sequence Segmentation by a Mixture of Switching Variable Memory Markov Sources (YS, GB, NT), pp. 513–520.
ICMLICML-2001-ZinkevichB #learning #multi #process #symmetry
Symmetry in Markov Decision Processes and its Implications for Single Agent and Multiagent Learning (MZ, TRB), p. 632–?.
SIGIRSIGIR-2001-BleiM #segmentation #topic
Topic Segmentation with an Aspect Hidden Markov Model (DMB, PJM), pp. 343–348.
SIGIRSIGIR-2001-ConroyO #modelling #summary
Text Summarization via Hidden Markov Models (JMC, DPO), pp. 406–407.
SACSAC-2001-LarocheBS #composition #process
A new decomposition technique for solving Markov decision processes (PL, YB, RS), pp. 12–16.
STOCSTOC-2001-MontenegroS #agile #geometry
Edge isoperimetry and rapid mixing on matroids and geometric Markov chains (RM, JBS), pp. 704–711.
CSLCSL-2001-KopylovN #type system
Markov’s Principle for Propositional Type Theory (AK, AN), pp. 570–584.
ICMLICML-2000-LiB #approach #clustering #modelling #using
A Bayesian Approach to Temporal Data Clustering using Hidden Markov Models (CL, GB), pp. 543–550.
ICMLICML-2000-McCallumFP #information management #modelling #segmentation
Maximum Entropy Markov Models for Information Extraction and Segmentation (AM, DF, FCNP), pp. 591–598.
ICPRICPR-v1-2000-AricaY
A Shape Descriptor Based on Circular Hidden Markov Mode (NA, FTYV), pp. 1924–1927.
ICPRICPR-v1-2000-BojovicS #modelling #recognition #word
Training of Hidden Markov Models for Cursive Handwritten Word Recognition (MB, MDS), pp. 1973–1976.
ICPRICPR-v1-2000-KamijoMIS #random #robust
Occlusion Robust Tracking Utilizing Spatio-Temporal Markov Random Field Model (SK, YM, KI, MS), pp. 1140–1144.
ICPRICPR-v1-2000-MossH #monte carlo #using
Alignment and Correspondence Using Markov Chain Monte Carlo (SM, ERH), pp. 1928–1931.
ICPRICPR-v2-2000-DehghanFAS #fuzzy #modelling #recognition #using #word
Off-Line Unconstrained Farsi Handwritten Word Recognition Using Fuzzy Vector Quantization and Hidden Markov Word Models (MD, KF, MA, MS), pp. 2351–2354.
ICPRICPR-v2-2000-WangZCF #approach #random #recognition
Hidden Markov Random Field Based Approach for Off-Line Handwritten Chinese Character Recognition (QW, RZ, ZC, DDF), pp. 2347–2350.
ICPRICPR-v3-2000-DeMenthonDS #distance #image #modelling #using
Image Distance Using Hidden Markov Models (DD, DSD, MVS), pp. 3147–3150.
ICPRICPR-v3-2000-GravierSC #automation #random #recognition #speech
A Markov Random Field Model for Automatic Speech Recognition (GG, MS, GC), pp. 3258–3261.
ICPRICPR-v3-2000-OukilS #algorithm #energy #random
Markovian Random Fields Energy Minimization Algorithms (AO, AS), pp. 3522–3525.
ICPRICPR-v3-2000-PagetL #analysis #parametricity #random #testing
Nonparametric Markov Random Field Model Analysis of the MeasTex Test Suite (RP, IDL), pp. 3939–3942.
KDDKDD-2000-GeS #pattern matching
Deformable Markov model templates for time-series pattern matching (XG, PS), pp. 81–90.
TACASTACAS-2000-HermannsKMS #model checking
A Markov Chain Model Checker (HH, JPK, JMK, MS), pp. 347–362.
CAVCAV-2000-BaierHHK #analysis #model checking
Model Checking Continuous-Time Markov Chains by Transient Analysis (CB, BRH, HH, JPK), pp. 358–372.
LICSLICS-2000-DesharnaisGJP #approximate #process
Approximating Labeled Markov Processes (JD, VG, RJ, PP), pp. 95–106.
ICDARICDAR-1999-KosmalaRLP #graph grammar #modelling #online #recognition #using
On-Line Handwritten Formula Recognition using Hidden Markov Models and Context Dependent Graph Grammars (AK, GR, SL, LP), pp. 107–110.
ICDARICDAR-1999-SuralD99a #documentation #image
A Two-state Markov Chain Model of Degraded Document Images (SS, PKD), pp. 463–466.
ICALPICALP-1999-Clote
Protein Folding, the Levinthal Paradox and Rapidly Mixing Markov Chains (PC), pp. 240–249.
ICMLICML-1999-FiroiuC #modelling #using
Abstracting from Robot Sensor Data using Hidden Markov Models (LF, PRC), pp. 106–114.
ICMLICML-1999-ThrunLF #learning #modelling #monte carlo #parametricity #probability #process
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes (ST, JL, DF), pp. 415–424.
ICMLICML-1999-WangM #optimisation #process
Hierarchical Optimization of Policy-Coupled Semi-Markov Decision Processes (GW, SM), pp. 464–473.
SIGIRSIGIR-1999-MillerLS #information retrieval
A Hidden Markov Model Information Retrieval System (DRHM, TL, RMS), pp. 214–221.
DACDAC-1999-QiuP #power management #process
Dynamic Power Management Based on Continuous-Time Markov Decision Processes (QQ, MP), pp. 555–561.
STOCSTOC-1999-CharikarKRRT #on the
On targeting Markov segments (MC, RK, PR, SR, AT), pp. 99–108.
STOCSTOC-1999-ChenLP
Lifting Markov Chains to Speed up Mixing (FC, LL, IP), pp. 275–281.
CAVCAV-1999-HermannsMS #analysis #composition #modelling #named #performance #specification
TIPPtool: Compositional Specification and Analysis of Markovian Performance Models (HH, VM, MS), pp. 487–490.
ICMLICML-1998-LochS #policy #process #using
Using Eligibility Traces to Find the Best Memoryless Policy in Partially Observable Markov Decision Processes (JL, SPS), pp. 323–331.
ICMLICML-1998-PendrithM #analysis #learning
An Analysis of Direct Reinforcement Learning in Non-Markovian Domains (MDP, MM), pp. 421–429.
ICPRICPR-1998-DolfingAO #modelling #online #verification
On-line signature verification with hidden Markov models (JGAD, EHLA, JJGMVO), pp. 1309–1312.
ICPRICPR-1998-EickelerKR #gesture #modelling #online #recognition
Hidden Markov model based continuous online gesture recognition (SE, AK, GR), pp. 1206–1208.
ICPRICPR-1998-GoktepeAYY #image #modelling #random #segmentation #using
Unsupervised texture based image segmentation by simulated annealing using Markov random field and Potts models (MG, VA, NY, CY), pp. 820–822.
ICPRICPR-1998-KamathKDD #image #modelling #segmentation #using
Joint segmentation and image interpretation using hidden Markov models (NK, KSK, UBD, RD), pp. 1840–1842.
ICPRICPR-1998-KnerrA #hybrid #recognition #word
A neural network-hidden Markov model hybrid for cursive word recognition (SK, EA), pp. 1518–1520.
ICPRICPR-1998-PagetL #multi #parametricity #random #recognition #synthesis
Texture synthesis and unsupervised recognition with a nonparametric multiscale Markov random field model (RP, DL), pp. 1068–1070.
ICPRICPR-1998-ProcterIE #modelling #recognition #string #using
The recognition of handwritten digit strings of unknown length using hidden Markov models (SP, JI, AJE), pp. 1515–1517.
ICPRICPR-1998-RigollK #comparison #modelling #online #verification
A systematic comparison between on-line and off-line methods for signature verification with hidden Markov models (GR, AK), pp. 1755–1757.
ICPRICPR-1998-WangLL #classification #composition #modelling #random #using
Texture classification using wavelet decomposition with Markov random field models (LW, JL, SZL), pp. 1613–1615.
DACDAC-1998-XieB #classification #finite #performance
Efficient State Classification of Finite State Markov Chains (AX, PAB), pp. 605–610.
LICSLICS-1998-DesharnaisEP #bisimulation #logic #process
A Logical Characterization of Bisimulation for Labeled Markov Processes (JD, AE, PP), pp. 478–487.
ICDARICDAR-1997-Aufmuth
Revealing the hidden Markov recognizer (CA), pp. 560–563.
ICDARICDAR-1997-FrankeGKM #classification #comparison #modelling #polynomial #recognition
A Comparison of Gaussian Distribution and Polynomial Classifiers in a Hidden Markov Model Based System for the Recognition of Cursive Script (JF, JMG, AK, EM), pp. 515–518.
ICDARICDAR-1997-KashiHNT #online #using #verification
On-line Handwritten Signature Verification using Hidden Markov Model Features (RSK, JH, WLN, WT), pp. 253–257.
ICDARICDAR-1997-KosmalaRR #modelling #online #recognition #using
Improved On-Line Handwriting Recognition Using Context Dependent Hidden Markov Models (AK, JR, GR), pp. 641–644.
ICDARICDAR-1997-MiledOCL #recognition
Coupling observation/letter for a Markovian modelisation applied to the recognition of Arabic handwriting (HM, CO, MC, YL), pp. 580–583.
ICDARICDAR-1997-OlivierJA #optimisation #order #recognition
Markov Model Order Optimization for Text Recognition (CO, FJ, MA), pp. 548–551.
ICMLICML-1997-SuematsuHL #approach #learning
A Bayesian Approach to Model Learning in Non-Markovian Environments (NS, AH, SL), pp. 349–357.
STOCSTOC-1997-Fill #algorithm
An Interruptible Algorithm for Perfect Sampling via Markov Chains (JAF), pp. 688–695.
LICSLICS-1997-BluteDEP #bisimulation #process
Bisimulation for Labelled Markov Processes (RB, JD, AE, PP), pp. 149–158.
ICPRICPR-1996-AmaraB #modelling #recognition
Printed PAW recognition based on planar hidden Markov models (NEBA, AB), pp. 220–224.
ICPRICPR-1996-CooperHY #random
A Markov random field model of subjective contour perception (PRC, SH, PY), pp. 100–104.
ICPRICPR-1996-DarrellP #gesture #process #recognition #using
Active gesture recognition using partially observable Markov decision processes (TD, AP), pp. 984–988.
ICPRICPR-1996-DelagnesB #graph #image #random
Rectilinear structure extraction in textured images with an irregular, graph-based Markov random field model (PD, DB), pp. 800–804.
ICPRICPR-1996-Draper #modelling #process #recognition
Modeling object recognition as a Markov decision process (BAD), pp. 95–99.
ICPRICPR-1996-GoktepeYA #segmentation
Unsupervised segmentation of gray level Markov model textures with hierarchical self organizing maps (MG, NY, VA), pp. 90–94.
ICPRICPR-1996-GonzalezC #classification #functional #random
The Markov random fields in functional neighbors as a texture model: applications in texture classification (AMG, DC), pp. 815–819.
ICPRICPR-1996-MorimotoYD #gesture #modelling #recognition #using
Recognition of head gestures using hidden Markov models (CM, YY, LSD), pp. 461–465.
ICPRICPR-1996-Nouza #feature model #modelling #recognition #speech
Feature selection methods for hidden Markov model-based speech recognition (JN), pp. 186–190.
ICPRICPR-1996-RigollKRN #comparison #modelling #recognition
A comparison between continuous and discrete density hidden Markov models for cursive handwriting recognition (GR, AK, JR, CN), pp. 205–209.
ICPRICPR-1996-SmitsD #adaptation #approach #image #random #segmentation #using
Information fusion in a Markov random field-based image segmentation approach using adaptive neighbourhoods (PCS, SGD), pp. 570–575.
KDDKDD-1996-StolorzC #learning #monte carlo #visual notation
Harnessing Graphical Structure in Markov Chain Monte Carlo Learning (PES, PCC), pp. 134–139.
DACDAC-1996-JohnsonCB #design #metric #process #simulation
Application of a Markov Model to the Measurement, Simulation, and Diagnosis of an Iterative Design Process (EWJ, LAC, JBB), pp. 185–188.
CAVCAV-1996-AzizSSB #verification
Verifying Continuous Time Markov Chains (AA, KS, VS, RKB), pp. 269–276.
ICDARICDAR-v1-1995-ChenWB #comparison #image #modelling
A comparison of discrete and continuous hidden Markov models for phrase spotting in text images (FC, LW, DSB), pp. 398–402.
ICDARICDAR-v1-1995-Garcia-SalicettiDGMF #online #predict #recognition
A hidden Markov model extension of a neural predictive system for on-line character recognition (SGS, BD, PG, AM, DF), pp. 50–53.
ICDARICDAR-v1-1995-GillouxLL #hybrid #network #recognition #word
A hybrid radial basis function network/hidden Markov model handwritten word recognition system (MG, BL, ML), pp. 394–397.
ICDARICDAR-v1-1995-GuyonP #design #memory management #modelling #using
Design of a linguistic postprocessor using variable memory length Markov models (IG, FP), pp. 454–457.
ICDARICDAR-v1-1995-ParkL #random #recognition
Hidden Markov mesh random field: theory and its application to handwritten character recognition (HSP, SWL), pp. 409–412.
ICDARICDAR-v2-1995-BouchaffraM #approach #information retrieval #random
A Markovian random field approach to information retrieval (DB, JGM), pp. 997–1002.
ICDARICDAR-v2-1995-OhK #modelling #recognition #using
Off-line recognition of handwritten Korean and alphanumeric characters using hidden Markov models (CO, WSK), pp. 815–818.
STOCSTOC-1995-LovaszW #performance
Efficient stopping rules for Markov chains (LL, PW), pp. 76–82.
ICMLICML-1994-Littman #framework #game studies #learning #multi
Markov Games as a Framework for Multi-Agent Reinforcement Learning (MLL), pp. 157–163.
ICMLICML-1994-SinghJJ #learning #process
Learning Without State-Estimation in Partially Observable Markovian Decision Processes (SPS, TSJ, MIJ), pp. 284–292.
SIGIRSIGIR-1994-MittendorfS #documentation #modelling #retrieval
Document and Passage Retrieval Based on Hidden Markov Models (EM, PS), pp. 318–327.
PDPPDP-1994-Siegle #modelling #parallel #process #source code
Reduced Markov Models Of Parallel Programs With Replicated Processes (MS), pp. 126–133.
ICDARICDAR-1993-AgazziK #2d #documentation #image #modelling #normalisation #pseudo #recognition #using
Joint normalization and recognition of degraded document images using pseudo-2D hidden Markov models (OEA, SsK), pp. 155–158.
ICDARICDAR-1993-ChenWB #detection #image #keyword #modelling #using
Detecting and locating partially specified keywords in scanned images using hidden Markov models (FC, LW, DSB), pp. 133–138.
ICDARICDAR-1993-GillouxLB #modelling #recognition #using #word
Strategies for handwritten words recognition using hidden Markov models (MG, ML, JMB), pp. 299–304.
ICDARICDAR-1993-KaltenmeierCGM #modelling #recognition
Sophisticated topology of hidden Markov models for cursive script recognition (AK, TC, JMG, EM), pp. 139–142.
ICDARICDAR-1993-LamH #modelling #using
Reading constrained text using hierarchical hidden Markov models (SWL, WKH), pp. 151–154.
ICDARICDAR-1993-LeeTC #recognition
A Markov language model in Chinese text recognition (HJL, CHT, CHCC), pp. 72–75.
STOCSTOC-1993-CoffmanJSW #analysis #proving
Markov chains, computer proofs, and average-case analysis of best fit bin packing (EGCJ, DSJ, PWS, RRW), pp. 412–421.
ICALPICALP-1990-CourcoubetisY #process
Markov Decision Processes and Regular Events (CC, MY), pp. 336–349.
STOCSTOC-1988-JerrumS #agile #approximate
Conductance and the Rapid Mixing Property for Markov Chains: the Approximation of the Permanent Resolved (MJ, AS), pp. 235–244.
SOSPSOSP-J-1975-ChuO76 #algorithm #analysis
Analysis of the PFF Replacement Algorithm via a Semi-Markov Model (WWC, HO), pp. 298–304.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
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