Stem sampl$ (all stems)

544 papers:

DATE-2015-HuangLH #multi

Volume-oriented sample preparation for reactant minimization on flow-based microfluidic biochips with multi-segment mixers (CMH, CHL, JDH), pp. 1114–1119.

HT-2015-SampsonMML #clustering #keyword #twitter

Surpassing the Limit: Keyword Clustering to Improve Twitter Sample Coverage (JS, FM, RM, HL), pp. 237–245.

PODS-2015-HuQT #memory management

External Memory Stream Sampling (XH, MQ, YT), pp. 229–239.

VLDB-2015-KimBPIMR #agile #visualisation

Rapid Sampling for Visualizations with Ordering Guarantees (AK, EB, AGP, PI, SM, RR), pp. 521–532.

VLDB-2015-NaziZT0D #network #online #performance #social

Walk, Not Wait: Faster Sampling Over Online Social Networks (AN, ZZ, ST, NZ, GD), pp. 678–689.

VLDB-2015-Zhou0D #network #online #performance #social

Leveraging History for Faster Sampling of Online Social Networks (ZZ, NZ, GD), pp. 1034–1045.

TACAS-2015-HansenWCNK #model checking #semantics #statistics

Semantic Importance Sampling for Statistical Model Checking (JPH, LW, SC, DdN, MHK), pp. 241–255.

TACAS-2015-UnnoT #horn clause #recursion

Inferring Simple Solutions to Recursion-Free Horn Clauses via Sampling (HU, TT), pp. 149–163.

MSR-2015-MartinHJSZ #mining #problem

The App Sampling Problem for App Store Mining (WM, MH, YJ, FS, YZ), pp. 123–133.

STOC-2015-AggarwalDRS #problem #using

Solving the Shortest Vector Problem in 2n Time Using Discrete Gaussian Sampling: Extended Abstract (DA, DD, OR, NSD), pp. 733–742.

STOC-2015-CohenP

Lp Row Sampling by Lewis Weights (MBC, RP), pp. 183–192.

CSCW-2015-ReineckeG #named #online #scalability

LabintheWild: Conducting Large-Scale Online Experiments With Uncompensated Samples (KR, KZG), pp. 1364–1378.

CSCW-2015-VashisthaCT

Increasing the Reach of Snowball Sampling: The Impact of Fixed versus Lottery Incentives (AV, EC, WT), pp. 1359–1363.

DHM-EH-2015-LiuCKQF #data analysis #power management

Balancing Power Consumption and Data Analysis Accuracy Through Adjusting Sampling Rates: Seeking for the Optimal Configuration of Inertial Sensors for Power Wheelchair Users (TL, CC, MK, GQ, JF), pp. 184–192.

DHM-HM-2015-SugimotoTNG #comparison #eye tracking #process

Comparison of Eye Movement During the Polishing Process of Metallographic Sample Between Expert and Nonexpert (TS, YT, HN, AG), pp. 399–410.

DHM-HM-2015-SugimotoYNG #analysis #process

EMG Activity Analysis of Expert Skills on Handheld Grinding Work for Metallographic Sample (TS, HY, HN, AG), pp. 165–173.

ICEIS-v1-2015-SarmentoCG #network #streaming #using

Streaming Networks Sampling using top-K Networks (RS, MC, JG), pp. 228–234.

ECIR-2015-Kelly #analysis #estimation #information retrieval #statistics

Statistical Power Analysis for Sample Size Estimation in Information Retrieval Experiments with Users (DK), pp. 822–825.

ICML-2015-KomiyamaHN #analysis #multi #probability #problem

Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays (JK, JH, HN), pp. 1152–1161.

ICML-2015-KuklianskyS #linear #performance

Attribute Efficient Linear Regression with Distribution-Dependent Sampling (DK, OS), pp. 153–161.

ICML-2015-WangFS #for free #monte carlo #privacy #probability

Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo (YXW, SEF, AJS), pp. 2493–2502.

ICML-2015-Yang0JZ #bound #fault #set

An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection (TY, LZ, RJ, SZ), pp. 135–143.

ICML-2015-ZhaoZ #optimisation #probability

Stochastic Optimization with Importance Sampling for Regularized Loss Minimization (PZ, TZ), pp. 1–9.

ICML-2015-ZhuG #complexity #robust #towards

Towards a Lower Sample Complexity for Robust One-bit Compressed Sensing (RZ, QG), pp. 739–747.

KDD-2015-ChenXZX

Differentially Private High-Dimensional Data Publication via Sampling-Based Inference (RC, QX, YZ, JX), pp. 129–138.

KDD-2015-Cohen #statistics

Stream Sampling for Frequency Cap Statistics (EC), pp. 159–168.

KDD-2015-IkonomovskaJD #predict #realtime #using

Real-Time Bid Prediction using Thompson Sampling-Based Expert Selection (EI, SJ, AD), pp. 1869–1878.

KDD-2015-LanH #complexity #learning #multi

Reducing the Unlabeled Sample Complexity of Semi-Supervised Multi-View Learning (CL, JH), pp. 627–634.

KDD-2015-Li #consistency

0-Bit Consistent Weighted Sampling (PL), pp. 665–674.

KDD-2015-LimK #graph #named

MASCOT: Memory-efficient and Accurate Sampling for Counting Local Triangles in Graph Streams (YL, UK), pp. 685–694.

KDD-2015-MitzenmacherPPT #clique #detection #network #scalability

Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling (MM, JP, RP, CET, SCX), pp. 815–824.

KDD-2015-RiondatoU #mining

Mining Frequent Itemsets through Progressive Sampling with Rademacher Averages (MR, EU), pp. 1005–1014.

KDD-2015-RiondatoU15a #algorithm #learning #statistics

VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms (MR, EU), pp. 2321–2322.

SEKE-2015-GaoKN #set

Combining Feature Subset Selection and Data Sampling for Coping with Highly Imbalanced Software Data (KG, TMK, AN), pp. 439–444.

SIGIR-2015-Baeza-Yates #incremental #query

Incremental Sampling of Query Logs (RABY), pp. 1093–1096.

SAC-2015-HsiehNKC #approximate #performance #query #recommendation

Efficient approximate thompson sampling for search query recommendation (CCH, JN, TK, JC), pp. 740–746.

SAC-2015-SantosOCFTT #named #similarity

Combine-and-conquer: improving the diversity in similarity search through influence sampling (LFDS, WDO, LOC, MRPF, AJMT, CTJ), pp. 994–999.

ESEC-FSE-2015-BorgesFdP #execution #probability #symbolic computation

Iterative distribution-aware sampling for probabilistic symbolic execution (MB, AF, Md, CSP), pp. 866–877.

SPLC-2015-ReulingBRLK #effectiveness #generative #product line #testing

Fault-based product-line testing: effective sample generation based on feature-diagram mutation (DR, JB, SR, ML, UK), pp. 131–140.

CASE-2014-HoussemanDRP #reduction

Smart dynamic sampling for wafer at risk reduction in semiconductor manufacturing (SH, SDP, GRV, JP), pp. 780–785.

CASE-2014-HuiM #assessment #performance #reduction

Performance assessment of virtual metrology in APC applications for the viability of sampling reductions (KH, JM), pp. 750–755.

DAC-2014-ChenPCWMYZC #manycore #named #parallel #simulation #thread

DAPs: Dynamic Adjustment and Partial Sampling for Multithreaded/Multicore Simulation (CCC, YCP, CFC, WSW, QM, PCY, WZ, TFC), p. 6.

DATE-2014-HenselK #energy

The energy benefit of level-crossing sampling including the actuator’s energy consumption (BH, KK), pp. 1–4.

DATE-2014-YuSHEAB #estimation #performance #physics

Efficient performance estimation with very small sample size via physical subspace projection and maximum a posteriori estimation (LY, SS, CH, IME, DAA, DSB), pp. 1–6.

PODS-2014-HuQT #independence

Independent range sampling (XH, MQ, YT), pp. 246–255.

SIGMOD-2014-LevinK #network #pipes and filters #social #using

Stratified-sampling over social networks using mapreduce (RL, YK), pp. 863–874.

SIGMOD-2014-WangKFGKM #framework #performance #query

A sample-and-clean framework for fast and accurate query processing on dirty data (JW, SK, MJF, KG, TK, TM), pp. 469–480.

VLDB-2014-JayachandranTKN #execution #interactive #query

Combining User Interaction, Speculative Query Execution and Sampling in the DICE System (PJ, KT, NK, AN), pp. 1697–1700.

VLDB-2014-YanCZ #bound

Error-bounded Sampling for Analytics on Big Sparse Data (YY, LJC, ZZ), pp. 1508–1519.

STOC-2014-ColeR #complexity

The sample complexity of revenue maximization (RC, TR), pp. 243–252.

ICALP-v1-2014-Ben-SassonRTW #algorithm #proving

Sampling-Based Proofs of Almost-Periodicity Results and Algorithmic Applications (EBS, NRZ, MT, JW), pp. 955–966.

LATA-2014-Khanna #random

Matchings, Random Walks, and Sampling (SK), pp. 32–33.

CHI-2014-FerreiraFK #visualisation

Sample-oriented task-driven visualizations: allowing users to make better, more confident decisions (NF, DF, ACK), pp. 571–580.

CHI-2014-LeivaS #empirical #set

Representatively memorable: sampling the right phrase set to get the text entry experiment right (LAL, GST), pp. 1709–1712.

CHI-2014-YueLCSBGSZ #experience #research

Photographing information needs: the role of photos in experience sampling method-style research (ZY, EL, CJC, JS, KB, ZG, NS, G(Z), pp. 1545–1554.

DHM-2014-SugimotoYG #analysis

Analysis of Expert Skills on Handheld Grinding Work for Metallographic Sample (TS, HY, AG), pp. 66–77.

DUXU-DI-2014-MuukkonenHLV #mobile #process

Tracking Mobile Workers’ Daily Activities with the Contextual Activity Sampling System (HM, KH, SL, MV), pp. 289–300.

DUXU-TMT-2014-LaamanenSH #design #process

Tracing Design Work through Contextual Activity Sampling (TKL, PSH, KH), pp. 142–152.

CIKM-2014-BudaCMK #database #named #performance

VFDS: An Application to Generate Fast Sample Databases (TSB, TC, JM, MK), pp. 2048–2050.

CIKM-2014-LiZLW #classification #probability

Probabilistic Classifier Chain Inference via Gibbs Sampling (LL, LZ, GL, HW), pp. 1855–1858.

CIKM-2014-RahmanH #network #strict #using

Sampling Triples from Restricted Networks using MCMC Strategy (MR, MAH), pp. 1519–1528.

CIKM-2014-ZhangZZLM #comprehension #constraints #matrix

Understanding the Sparsity: Augmented Matrix Factorization with Sampled Constraints on Unobservables (YZ, MZ, YZ, YL, SM), pp. 1189–1198.

ICML-c1-2014-GopalanMM #online #problem

Thompson Sampling for Complex Online Problems (AG, SM, YM), pp. 100–108.

ICML-c2-2014-BachmanFP #approximate

Sample-based approximate regularization (PB, AMF, DP), pp. 1926–1934.

ICML-c2-2014-DaneshmandGSS #algorithm #complexity #network

Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm (HD, MGR, LS, BS), pp. 793–801.

ICML-c2-2014-GrandeWH #learning #performance #process

Sample Efficient Reinforcement Learning with Gaussian Processes (RCG, TJW, JPH), pp. 1332–1340.

ICML-c2-2014-TaylorGP #analysis #approximate #linear #programming

An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy (GT, CG, DP), pp. 451–459.

ICPR-2014-AlmogahedK #game studies #named #using

NEATER: Filtering of Over-sampled Data Using Non-cooperative Game Theory (BAA, IAK), pp. 1371–1376.

ICPR-2014-GeDGC #learning

Background Subtraction with Dynamic Noise Sampling and Complementary Learning (WG, YD, ZG, YC), pp. 2341–2346.

ICPR-2014-MarteauGR #gesture #kernel #performance #recognition

Down-sampling Coupled to Elastic Kernel Machines for Efficient Recognition of Isolated Gestures (PFM, SG, CR), pp. 363–368.

ICPR-2014-NguyenP #linear #multi #using

Tracking Using Multiple Linear Searches and Motion Direction Sampling (TN, TPP), pp. 2191–2196.

ICPR-2014-SandhanC #dataset #hybrid #pattern matching #pattern recognition #recognition

Handling Imbalanced Datasets by Partially Guided Hybrid Sampling for Pattern Recognition (TS, JYC), pp. 1449–1453.

ICPR-2014-YangYH #learning

Diversity-Based Ensemble with Sample Weight Learning (CY, XCY, HWH), pp. 1236–1241.

ICPR-2014-YuCK #distance #recognition #set #using

Pill Recognition Using Imprint Information by Two-Step Sampling Distance Sets (JY, ZC, SiK), pp. 3156–3161.

KDD-2014-AhmedDNK #framework #graph

Graph sample and hold: a framework for big-graph analytics (NKA, NGD, JN, RRK), pp. 1446–1455.

KDD-2014-ChengL #equivalence #parallel #process

Parallel gibbs sampling for hierarchical dirichlet processes via gamma processes equivalence (DC, YL), pp. 562–571.

KDD-2014-Cohen #distance #performance #query

Distance queries from sampled data: accurate and efficient (EC), pp. 681–690.

KDD-2014-CormodeD #big data #tutorial

Sampling for big data: a tutorial (GC, NGD), p. 1975.

KDD-2014-DundarYR #identification #towards

Batch discovery of recurring rare classes toward identifying anomalous samples (MD, HZY, BR), pp. 223–232.

KDD-2014-GaddeAO #graph #learning #using

Active semi-supervised learning using sampling theory for graph signals (AG, AA, AO), pp. 492–501.

KDD-2014-LiARS #complexity #modelling #topic

Reducing the sampling complexity of topic models (AQL, AA, SR, AJS), pp. 891–900.

KDD-2014-PapailiopoulosKB

Provable deterministic leverage score sampling (DSP, ATK, CB), pp. 997–1006.

SEKE-2014-FinlayPC #predict

Synthetic Minority Over-sampling TEchnique (SMOTE) for Predicting Software Build Outcomes (JF, RP, AMC), pp. 546–551.

SEKE-2014-GaoKN #estimation #learning #quality #ranking

Comparing Two Approaches for Adding Feature Ranking to Sampled Ensemble Learning for Software Quality Estimation (KG, TMK, AN), pp. 280–285.

SIGIR-2014-Voorhees #metric

The effect of sampling strategy on inferred measures (EMV), pp. 1119–1122.

SAC-2014-JunAK #detection #using

DDoS attack detection by using packet sampling and flow features (JHJ, CWA, SHK), pp. 711–712.

SAC-2014-KimKYP #network #online #social

Sampling in online social networks (SWK, KNK, SHY, SP), pp. 845–849.

SAC-2014-WangEB #evolution #orthogonal

Mirrored orthogonal sampling with pairwise selection in evolution strategies (HW, ME, TB), pp. 154–156.

FSE-2014-FilieriPVG #execution #statistics #symbolic computation

Statistical symbolic execution with informed sampling (AF, CSP, WV, JG), pp. 437–448.

ICST-2014-PapadakisHT #analysis #combinator #interactive #mutation testing #testing

Sampling Program Inputs with Mutation Analysis: Going Beyond Combinatorial Interaction Testing (MP, CH, YLT), pp. 1–10.

CASE-2013-ChenHCHW #automation #maintenance #predict

Automatic baseline-sample-selection scheme for baseline predictive maintenance (CFC, YSH, FTC, HCH, SCW), pp. 183–188.

CASE-2013-KurzDP #monitoring #reliability

Monitoring virtual metrology reliability in a sampling decision system (DK, CDL, JP), pp. 20–25.

DAC-2013-GuCL #estimation #performance #validation

Efficient moment estimation with extremely small sample size via bayesian inference for analog/mixed-signal validation (CG, EC, XL), p. 7.

DATE-2013-LiZCZ #analysis #multi #simulation

Multi-level phase analysis for sampling simulation (JL, WZ, HC, BZ), pp. 649–654.

DATE-2013-ParkCA #energy

Non-speculative double-sampling technique to increase energy-efficiency in a high-performance processor (JP, AC, JAA), pp. 254–257.

DATE-2013-YaoYW #adaptation #analysis #modelling #online #performance

Efficient importance sampling for high-sigma yield analysis with adaptive online surrogate modeling (JY, ZY, YW), pp. 1291–1296.

DRR-2013-LipskyLN #policy

Optimal policy for labeling training samples (LL, DPL, GN).

SIGMOD-2013-FanXS #adaptation #monitoring #named #performance #realtime

FAST: differentially private real-time aggregate monitor with filtering and adaptive sampling (LF, LX, VSS), pp. 1065–1068.

SIGMOD-2013-ZhangR #case study #scalability #towards

Towards high-throughput gibbs sampling at scale: a study across storage managers (CZ, CR), pp. 397–408.

VLDB-2013-NirkhiwaleDJ #algebra #estimation

A Sampling Algebra for Aggregate Estimation (SN, AD, CMJ), pp. 1798–1809.

VLDB-2013-PavanTTW #graph

Counting and Sampling Triangles from a Graph Stream (AP, KT, ST, KLW), pp. 1870–1881.

STOC-2013-BringmannL

Succinct sampling from discrete distributions (KB, KGL), pp. 775–782.

STOC-2013-Thorup #independence #set #similarity

Bottom-k and priority sampling, set similarity and subset sums with minimal independence (MT), pp. 371–380.

HCI-AMTE-2013-BorsciMB #assessment #data transformation

A Grounded Procedure for Managing Data and Sample Size of a Home Medical Device Assessment (SB, JLM, JB), pp. 166–175.

ICEIS-J-2013-RudraGA13a #approximate #query

Estimating Sufficient Sample Sizes for Approximate Decision Support Queries (AR, RPG, NRA), pp. 85–99.

ICEIS-v1-2013-RudraGA #approximate #query

Selecting Adequate Samples for Approximate Decision Support Queries (AR, RPG, NRA), pp. 46–55.

CIKM-2013-FangYZ #graph #scalability

Active exploration: simultaneous sampling and labeling for large graphs (MF, JY, XZ), pp. 829–834.

ICML-c1-2013-ZhuCPZ #algorithm #modelling #performance #topic

Gibbs Max-Margin Topic Models with Fast Sampling Algorithms (JZ, NC, HP, BZ), pp. 124–132.

ICML-c3-2013-Agarwal #algorithm #multi #predict

Selective sampling algorithms for cost-sensitive multiclass prediction (AA), pp. 1220–1228.

ICML-c3-2013-AgrawalG #linear

Thompson Sampling for Contextual Bandits with Linear Payoffs (SA, NG), pp. 127–135.

ICML-c3-2013-Busa-FeketeSCWH #adaptation

Top-k Selection based on Adaptive Sampling of Noisy Preferences (RBF, BS, WC, PW, EH), pp. 1094–1102.

ICML-c3-2013-LattimoreHS #learning

The Sample-Complexity of General Reinforcement Learning (TL, MH, PS), pp. 28–36.

ICML-c3-2013-Meng #random #scalability

Scalable Simple Random Sampling and Stratified Sampling (XM), pp. 531–539.

KDD-2013-ChiangLPY

Inferring distant-time location in low-sampling-rate trajectories (MFC, YHL, WCP, PSY), pp. 1454–1457.

KDD-2013-GetoorM13a #network

Network sampling (LG, AM), p. 1528.

KDD-2013-GuALH #classification #graph

Selective sampling on graphs for classification (QG, CCA, JL, JH), pp. 131–139.

KDD-2013-WangY #learning #query

Querying discriminative and representative samples for batch mode active learning (ZW, JY), pp. 158–166.

RecSys-2013-SilbermannBR #recommendation

Sample selection for MCMC-based recommender systems (TS, IB, SR), pp. 403–406.

SIGIR-2013-ZhangCWY #collaboration #optimisation

Optimizing top-n collaborative filtering via dynamic negative item sampling (WZ, TC, JW, YY), pp. 785–788.

ECOOP-2013-WuZSGSY #fault #optimisation #statistics

Simple Profile Rectifications Go a Long Way — Statistically Exploring and Alleviating the Effects of Sampling Errors for Program Optimizations (BW, MZ, XS, YG, RS, GY), pp. 654–678.

ESEC-FSE-2013-RahmanPHD #bias #fault #predict

Sample size vs. bias in defect prediction (FR, DP, IH, PTD), pp. 147–157.

CGO-2013-ChoMHBM #profiling

Instant profiling: Instrumentation sampling for profiling datacenter applications (HKC, TM, REH, DB, SAM), p. 10.

HPCA-2013-ArdestaniR #manycore #named #performance #using

ESESC: A fast multicore simulator using Time-Based Sampling (EKA, JR), pp. 448–459.

HPDC-2013-SuAWMWA #dataset #distributed #using

Taming massive distributed datasets: data sampling using bitmap indices (YS, GA, JW, KM, JW, JPA), pp. 13–24.

ISSTA-2013-Buda #database #generative #testing #using

Generation of test databases using sampling methods (TSB), pp. 366–369.

CASE-2012-KurzDP #using

Sampling Decision System in semiconductor manufacturing using Virtual Metrology (DK, CDL, JP), pp. 74–79.

DAC-2012-KuoHCKC #design #monte carlo #performance

Efficient trimmed-sample Monte Carlo methodology and yield-aware design flow for analog circuits (CCK, WYH, YHC, JFK, YKC), pp. 1113–1118.

DATE-2012-MaricauJG #analysis #learning #multi #reliability #using

Hierarchical analog circuit reliability analysis using multivariate nonlinear regression and active learning sample selection (EM, DdJ, GGEG), pp. 745–750.

PODS-2012-McGregorPTW #estimation #statistics

Space-efficient estimation of statistics over sub-sampled streams (AM, AP, ST, DPW), pp. 273–282.

SIGMOD-2012-QianCJ

Sample-driven schema mapping (LQ, MJC, HVJ), pp. 73–84.

SIGMOD-2012-RosnerHGPB #correlation #performance #word

Fast sampling word correlations of high dimensional text data (abstract only) (FR, AH, MG, MP, AB), p. 866.

SIGMOD-2012-SarmaLGMH #performance #scalability

Efficient spatial sampling of large geographical tables (ADS, HL, HG, JM, AYH), pp. 193–204.

ITiCSE-2012-FletcherG #object-oriented #programming

Sample courseware for introductory OO programming (RF, RG), p. 370.

TACAS-2012-BarbotHP #model checking #statistics

Coupling and Importance Sampling for Statistical Model Checking (BB, SH, CP), pp. 331–346.

PLDI-2012-GodefroidT #automation #encoding #synthesis

Automated synthesis of symbolic instruction encodings from I/O samples (PG, AT), pp. 441–452.

ICALP-v1-2012-BringmannP #performance

Efficient Sampling Methods for Discrete Distributions (KB, KP), pp. 133–144.

ICALP-v1-2012-LaekhanukitGS #approach #problem

A Rounding by Sampling Approach to the Minimum Size k-Arc Connected Subgraph Problem (BL, SOG, MS), pp. 606–616.

CSCW-2012-TripathiB #experience #modelling #predict

Predicting creativity in the wild: experience sample and sociometric modeling of teams (PT, WB), pp. 1203–1212.

ICEIS-v1-2012-RudraGA #approximate #performance #query

An Efficient Sampling Scheme for Approximate Processing of Decision Support Queries (AR, RPG, NA), pp. 16–26.

ICEIS-v3-2012-HamadaASO #classification #documentation #taxonomy #using

A Classification Method of Open-ended Questionnaires using Category-based Dictionary from Sampled Documents (KH, MA, MS, HO), pp. 193–198.

CIKM-2012-BhuiyanMH #interactive #mining

Interactive pattern mining on hidden data: a sampling-based solution (MB, SM, MAH), pp. 95–104.

CIKM-2012-CaiZ #injection #learning #rank

Variance maximization via noise injection for active sampling in learning to rank (WC, YZ), pp. 1809–1813.

CIKM-2012-LiangZ #classification #performance

An efficient and simple under-sampling technique for imbalanced time series classification (GL, CZ), pp. 2339–2342.

CIKM-2012-OhY #framework #named

iSampling: framework for developing sampling methods considering user’s interest (JO, HY), pp. 1667–1671.

ICML-2012-AhnBW #probability

Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring (SA, AKB, MW), p. 230.

ICML-2012-AzarMK #complexity #generative #learning #on the

On the Sample Complexity of Reinforcement Learning with a Generative Model (MGA, RM, BK), p. 222.

ICML-2012-QuadriantoCL #clique #graph #persistent #set

The Most Persistent Soft-Clique in a Set of Sampled Graphs (NQ, CC, CHL), p. 32.

ICML-2012-VaroquauxGT #clustering #correlation #design

Small-sample brain mapping: sparse recovery on spatially correlated designs with randomization and clustering (GV, AG, BT), p. 178.

ICPR-2012-AbouelenienY #analysis #fault #named #performance

SampleBoost: Improving boosting performance by destabilizing weak learners based on weighted error analysis (MA, XY), pp. 585–588.

ICPR-2012-Filip

Restoring illumination and view dependent data from sparse samples (JF), pp. 1391–1394.

ICPR-2012-HanWHBR #generative #graph #probability

Sampling graphs from a probabilistic generative model (LH, RCW, ERH, LB, PR), pp. 1643–1646.

ICPR-2012-HuangH #invariant #using

Binary invariant cross color descriptor using galaxy sampling (GHH, CRH), pp. 2610–2613.

ICPR-2012-LiL12a #image #invariant #segmentation

Scale-invariant sampling for supervised image segmentation (YL, ML), pp. 1399–1402.

ICPR-2012-LiuCZZ

Fusion of low-and high-dimensional approaches by trackers sampling for generic human motion tracking (YL, JC, HZ, HZ), pp. 898–901.

ICPR-2012-LoWCC #3d #estimation #locality #people

Acceleration of vanishing point-based line sampling scheme for people localization and height estimation via 3D line sampling (KHL, CJW, JHC, HTC), pp. 2788–2791.

ICPR-2012-RaymondMOH #markov #network

Map matching with Hidden Markov Model on sampled road network (RR, TM, TO, NH), pp. 2242–2245.

ICPR-2012-RiechertZMK #estimation #hybrid #realtime #recursion #using

Real-time disparity estimation using line-wise hybrid recursive matching and cross-bilateral median up-sampling (CR, FZ, MM, PK), pp. 3168–3171.

ICPR-2012-TianC12a #image #optimisation #using

Depth image up-sampling using ant colony optimization (JT, LC), pp. 3795–3798.

KDD-2012-BellareIPR

Active sampling for entity matching (KB, SI, AGP, VR), pp. 1131–1139.

KDD-2012-BoleyMG #linear #using

Linear space direct pattern sampling using coupling from the past (MB, SM, TG), pp. 69–77.

KDD-2012-ChattopadhyayWFDPY #probability

Batch mode active sampling based on marginal probability distribution matching (RC, ZW, WF, ID, SP, JY), pp. 741–749.

KDD-2012-DasguptaKS #social

Social sampling (AD, RK, DS), pp. 235–243.

KDD-2012-LiZ

Sampling minimal frequent boolean (DNF) patterns (GL, MJZ), pp. 87–95.

OOPSLA-2012-BaoZZ #nondeterminism #program analysis

White box sampling in uncertain data processing enabled by program analysis (TB, YZ, XZ), pp. 897–914.

SAC-2012-ParkDNDKK #identification #memory management #named

HotDataTrap: a sampling-based hot data identification scheme for flash memory (DP, BKD, YN, DHCD, YK, YK), pp. 1610–1617.

SAC-2012-ZanioliFC #information management #named #static analysis

SAILS: static analysis of information leakage with sample (MZ, PF, AC), pp. 1308–1313.

LCTES-2012-ZuluagaKMP #design #predict

“Smart” design space sampling to predict Pareto-optimal solutions (MZ, AK, PAM, MP), pp. 119–128.

CAV-2012-JegourelLS #model checking #optimisation #parametricity #statistics

Cross-Entropy Optimisation of Importance Sampling Parameters for Statistical Model Checking (CJ, AL, SS), pp. 327–342.

CAV-2012-ZutshiST #abstraction #relational

Timed Relational Abstractions for Sampled Data Control Systems (AZ, SS, AT), pp. 343–361.

ISSTA-2012-ZhaiXCT #approach #named #parallel #thread

CARISMA: a context-sensitive approach to race-condition sample-instance selection for multithreaded applications (KZ, BX, WKC, THT), pp. 221–231.

LICS-2012-KomuravelliPC #learning #probability

Learning Probabilistic Systems from Tree Samples (AK, CSP, EMC), pp. 441–450.

DAC-2011-DongL #performance #predict

Efficient SRAM failure rate prediction via Gibbs sampling (CD, XL), pp. 200–205.

DATE-2011-LuJTL #architecture #parametricity #performance #simulation

Efficient parameter variation sampling for architecture simulations (FL, RJ, GT, SL), pp. 1578–1583.

DATE-2011-RoyBC

Waste-aware dilution and mixing of biochemical samples with digital microfluidic biochips (SR, BBB, KC), pp. 1059–1064.

ICDAR-2011-LouradourK #categorisation #documentation #feature model #image #performance

Sample-Dependent Feature Selection for Faster Document Image Categorization (JL, CK), pp. 309–313.

ICDAR-2011-WanLZ #online #recognition

On-line Chinese Character Recognition System for Overlapping Samples (XW, CL, YZ), pp. 799–803.

PODS-2011-CohenK #using

Get the most out of your sample: optimal unbiased estimators using partial information (EC, HK), pp. 13–24.

SIGMOD-2011-HuangWYL #algorithm #network

Sampling based algorithms for quantile computation in sensor networks (ZH, LW, KY, YL), pp. 745–756.

SIGMOD-2011-ZhangZD #corpus #estimation #mining #performance

Mining a search engine’s corpus: efficient yet unbiased sampling and aggregate estimation (MZ, NZ, GD), pp. 793–804.

VLDB-2011-CohenCD #flexibility #summary

Structure-Aware Sampling: Flexible and Accurate Summarization (EC, GC, NGD), pp. 819–830.

ICPC-2011-PanchenkoKPZ #database #precise #query #scalability #source code #using

Precise and Scalable Querying of Syntactical Source Code Patterns Using Sample Code Snippets and a Database (OP, JK, HP, AZ), pp. 41–50.

ICPC-2011-PirzadehSHM #concept #execution

The Concept of Stratified Sampling of Execution Traces (HP, SS, AHL, AM), pp. 225–226.

STOC-2011-ValiantV

Estimating the unseen: an n/log(n)-sample estimator for entropy and support size, shown optimal via new CLTs (GV, PV), pp. 685–694.

ICALP-v1-2011-ChakrabortyGM #performance

Efficient Sample Extractors for Juntas with Applications (SC, DGS, AM), pp. 545–556.

FM-2011-BonakdarpourNF #runtime #verification

Sampling-Based Runtime Verification (BB, SN, SF), pp. 88–102.

CHI-2011-Miller #architecture

Item sampling for information architecture (CSM), pp. 2211–2214.

CHI-2011-PaekH #set

Sampling representative phrase sets for text entry experiments: a procedure and public resource (TP, BJPH), pp. 2477–2480.

CSCW-2011-FetterG #experience #named

PRIMIExperience: experience sampling via instant messaging (MF, TG), pp. 629–632.

DUXU-v1-2011-SeoLL #development #experience #mobile

An Experience Sampling System for Context-Aware Mobile Application Development (JS, SL, GL), pp. 648–657.

CIKM-2011-BrauerRMB #information management #regular expression

Enabling information extraction by inference of regular expressions from sample entities (FB, RR, AM, WMB), pp. 1285–1294.

CIKM-2011-LinC #data fusion #learning #query

Query sampling for learning data fusion (TCL, PJC), pp. 141–146.

ICML-2011-DauphinGB #learning #re-engineering #scalability

Large-Scale Learning of Embeddings with Reconstruction Sampling (YD, XG, YB), pp. 945–952.

ICML-2011-GermainLLMS #approach #kernel

A PAC-Bayes Sample-compression Approach to Kernel Methods (PG, AL, FL, MM, SS), pp. 297–304.

ICML-2011-GhavamzadehLMH #analysis

Finite-Sample Analysis of Lasso-TD (MG, AL, RM, MWH), pp. 1177–1184.

ICML-2011-OrabonaC #algorithm

Better Algorithms for Selective Sampling (FO, NCB), pp. 433–440.

ICML-2011-Reyzin #predict

Boosting on a Budget: Sampling for Feature-Efficient Prediction (LR), pp. 529–536.

ICML-2011-WickRBCM #graph #named

SampleRank: Training Factor Graphs with Atomic Gradients (MLW, KR, KB, AC, AM), pp. 777–784.

KDD-2011-BoleyLPG #performance #random

Direct local pattern sampling by efficient two-step random procedures (MB, CL, DP, TG), pp. 582–590.

KDD-2011-ChenDWSNL #analysis #process

Activity analysis based on low sample rate smart meters (FC, JD, BW, SS, MRN, CTL), pp. 240–248.

KDD-2011-DalviKMR #nearest neighbour #using

Sampling hidden objects using nearest-neighbor oracles (NND, RK, AM, VR), pp. 1325–1333.

KDD-2011-KongFY #classification #graph

Dual active feature and sample selection for graph classification (XK, WF, PSY), pp. 654–662.

KDD-2011-MaiyaB #bias #network #towards

Benefits of bias: towards better characterization of network sampling (ASM, TYBW), pp. 105–113.

KDIR-2011-PrachuabsupakijS #classification #multi #set #using

Multi-class Data Classification for Imbalanced Data Set using Combined Sampling Approaches (WP, NS), pp. 166–171.

KMIS-2011-AndresLLC #assessment

Solvency Assessment in an Unbalanced Sample (JdA, PL, FSL, FJdCJ), pp. 283–286.

MLDM-2011-Kessl #mining #parallel #using

Static Load Balancing of Parallel Mining of Frequent Itemsets Using Reservoir Sampling (RK), pp. 553–567.

SEKE-2011-RadulovicG #modelling #quality #semantics

Extending Software Quality Models — A Sample In The Domain of Semantic Technologies (FR, RGC), pp. 25–30.

SIGIR-2011-HoobinPZ #corpus

Sample selection for dictionary-based corpus compression (CH, SJP, JZ), pp. 1137–1138.

ESEC-FSE-2011-CostacheKK #design #implementation #process #validation

Design and validation of feature-based process model tailoring: a sample implementation of PDE (DC, GK, MK), pp. 464–467.

LCTES-2011-ThomasFK #execution #monitoring

Lowering overhead in sampling-based execution monitoring and tracing (JJT, SF, DK), pp. 101–110.

CASE-2010-YuanZ #video

Micro-mixing of highly viscous bio-samples observed with a miniature wireless video sensor (LY, YFZ), pp. 180–185.

DAC-2010-SingheeC

Pareto sampling: choosing the right weights by derivative pursuit (AS, PC), pp. 913–916.

DATE-2010-JaffariA10a #analysis #correlation #performance #variability

Correlation controlled sampling for efficient variability analysis of analog circuits (JJ, MA), pp. 1305–1308.

DATE-2010-QaziTDSC #analysis #performance #reduction

Loop flattening & spherical sampling: Highly efficient model reduction techniques for SRAM yield analysis (MQ, MT, LD, DS, AC), pp. 801–806.

DATE-2010-VillenaS #named #order #reduction

HORUS — high-dimensional Model Order Reduction via low moment-matching upgraded sampling (JFV, LMS), pp. 465–470.

PODS-2010-CormodeMYZ #distributed

Optimal sampling from distributed streams (GC, SM, KY, QZ), pp. 77–86.

SIGMOD-2010-KohlerZSST

Sampling dirty data for matching attributes (HK, XZ, SWS, YS, KLT), pp. 63–74.

SIGMOD-2010-WuOT #multi #online #query

Continuous sampling for online aggregation over multiple queries (SW, BCO, KLT), pp. 651–662.

VLDB-2010-BeskalesIG #constraints #dependence #functional

Sampling the Repairs of Functional Dependency Violations under Hard Constraints (GB, IFI, LG), pp. 197–207.

ICSM-2010-ZhangW #quality

Sampling program quality (HZ, RW), pp. 1–10.

PASTE-2010-NarayanappaBR

Property-aware program sampling (HN, MSB, HR), pp. 45–52.

STOC-2010-Varadarajan #geometry #set

Weighted geometric set cover via quasi-uniform sampling (KRV), pp. 641–648.

CIKM-2010-BennettC #classification #online

Online stratified sampling: evaluating classifiers at web-scale (PNB, VRC), pp. 1581–1584.

CIKM-2010-KaliciakSWP #hybrid #image #novel #retrieval

Novel local features with hybrid sampling technique for image retrieval (LK, DS, NW, JP), pp. 1557–1560.

ICML-2010-LazaricGM10a #analysis

Finite-Sample Analysis of LSTD (AL, MG, RM), pp. 615–622.

ICPR-2010-ChakrabortyG #recognition #speech

Role of Synthetically Generated Samples on Speech Recognition in a Resource-Scarce Language (RC, UG), pp. 1618–1621.

ICPR-2010-LeeCL #algorithm #data-driven #graph #markov #monte carlo #using

A Graph Matching Algorithm Using Data-Driven Markov Chain Monte Carlo Sampling (JL, MC, KML), pp. 2816–2819.

ICPR-2010-RenHHLC #detection

A Sample Pre-mapping Method Enhancing Boosting for Object Detection (HR, XH, CKH, LL, XC), pp. 3005–3008.

ICPR-2010-ShangDJ #image

Compressive Sampling Recovery for Natural Images (FS, HD, YJ), pp. 2206–2209.

ICPR-2010-Strand

Interpolation and Sampling on a Honeycomb Lattice (RS), pp. 2222–2225.

ICPR-2010-Strand10a #3d #grid #re-engineering

Sampling and Ideal Reconstruction on the 3D Diamond Grid (RS), pp. 4609–4612.

ICPR-2010-TakalaCP #clustering #network #sequence

Boosting Clusters of Samples for Sequence Matching in Camera Networks (VT, YC, MP), pp. 400–403.

ICPR-2010-TanakaIKM #fault #kernel

A Relationship Between Generalization Error and Training Samples in Kernel Regressors (AT, HI, MK, MM), pp. 1421–1424.

ICPR-2010-ZhangW10a #modelling #random #validation

LLN-based Model-Driven Validation of Data Points for Random Sample Consensus Methods (LZ, DW), pp. 3436–3439.

OOPSLA-2010-JinTLL #concurrent #debugging

Instrumentation and sampling strategies for cooperative concurrency bug isolation (GJ, AVT, BL, SL), pp. 241–255.

SAC-2010-AquinoOW #algorithm #network

A wavelet-based sampling algorithm for wireless sensor networks applications (ALLdA, RARO, EFW), pp. 1604–1608.

SAC-2010-FernandesLR #classification #random

The impact of random samples in ensemble classifiers (PF, LL, DDAR), pp. 1002–1009.

SAC-2010-MahrsiPHR

Spatiotemporal sampling for trajectory streams (MKEM, CP, GH, FR), pp. 1627–1628.

CGO-2010-ChenVHLRYCZ #compilation #hardware

Taming hardware event samples for FDO compilation (DC, NV, RH, SwL, VR, PY, WC, WZ), pp. 42–52.

LCTES-2010-FischmeisterB #execution #monitoring

Sampling-based program execution monitoring (SF, YB), pp. 133–142.

ICLP-2010-Fierens10 #logic #modelling #performance #probability

Improving the Efficiency of Gibbs Sampling for Probabilistic Logical Models by Means of Program Specialization (DF), pp. 74–83.

ICST-2010-YanCZZZ #clustering #execution

A Dynamic Test Cluster Sampling Strategy by Leveraging Execution Spectra Information (SY, ZC, ZZ, CZ, YZ), pp. 147–154.

CASE-2009-BorgstromJBSK

Field-tests of a redundantly actuated cable-driven robot for environmental sampling applications (PHB, BLJ, MAB, GSS, WJK), pp. 615–620.

CASE-2009-ChenHB

Optimum sampling for track PEB CD Integrated Metrology (AC, SH, JB), pp. 439–442.

CASE-2009-YuanZ #using

Micro-mixing of highly viscous bio-samples using orbital shaking (LY, YFZ), pp. 579–584.

DAC-2009-VeetilSBSR #analysis #dependence #performance

Efficient smart sampling based full-chip leakage analysis for intra-die variation considering state dependence (VV, DS, DB, SS, SR), pp. 154–159.

DAC-2009-VillenaS #automation #modelling #multi #named

ARMS — automatic residue-minimization based sampling for multi-point modeling techniques (JFV, LMS), pp. 951–956.

ICDAR-2009-GalballyFMO #evaluation #using #verification

Evaluation of Brute-force Attack to Dynamic Signature Verification Using Synthetic Samples (JG, JF, MMD, JOG), pp. 131–135.

ICDAR-2009-GalballyFMO09a

Improving the Enrollment in Dynamic Signature Verfication with Synthetic Samples (JG, JF, MMD, JOG), pp. 1295–1299.

ICDAR-2009-LeungL #generative #recognition

Recognition of Handwritten Chinese Characters by Combining Regularization, Fisher’s Discriminant and Distorted Sample Generation (KCL, CHL), pp. 1026–1030.

PODS-2009-BravermanOZ

Optimal sampling from sliding windows (VB, RO, CZ), pp. 147–156.

VLDB-2009-CohenKS #coordination #multi

Coordinated Weighted Sampling for Estimating Aggregates Over Multiple Weight Assignments (EC, HK, SS), pp. 646–657.

VLDB-2009-HasanZ #graph

Output Space Sampling for Graph Patterns (MAH, MJZ), pp. 730–741.

TACAS-2009-MateescuW #adaptation

Hierarchical Adaptive State Space Caching Based on Level Sampling (RM, AW), pp. 215–229.

MSR-2009-Mockus #scalability #source code #towards #version control

Amassing and indexing a large sample of version control systems: Towards the census of public source code history (AM), pp. 11–20.

PLDI-2009-MarinoMN #concurrent #detection #effectiveness #lightweight #named

LiteRace: effective sampling for lightweight data-race detection (DM, MM, SN), pp. 134–143.

ICALP-v1-2009-AndoniIOR

External Sampling (AA, PI, KO, RR), pp. 83–94.

HCI-NT-2009-Lew #experience #what

What Do Users Really Do? Experience Sampling in the 21st Century (GSL), pp. 314–319.

CIKM-2009-ZhangXSYD #evaluation #learning #named

ROSE: retail outlet site evaluation by learning with both sample and feature preference (BZ, MX, JYS, WJY, JD), pp. 1397–1404.

ECIR-2009-DonmezC #learning #optimisation #rank

Active Sampling for Rank Learning via Optimizing the Area under the ROC Curve (PD, JGC), pp. 78–89.

ICML-2009-Cesa-BianchiGO #bound #classification #robust

Robust bounds for classification via selective sampling (NCB, CG, FO), pp. 121–128.

ICML-2009-Doshi-VelezG #process

Accelerated sampling for the Indian Buffet Process (FDV, ZG), pp. 273–280.

ICML-2009-KumarMT #approximate #composition #on the

On sampling-based approximate spectral decomposition (SK, MM, AT), pp. 553–560.

ICML-2009-SindhwaniML #design #nondeterminism

Uncertainty sampling and transductive experimental design for active dual supervision (VS, PM, RDL), pp. 953–960.

ICML-2009-ZhouSL #learning #multi

Multi-instance learning by treating instances as non-I.I.D. samples (ZHZ, YYS, YFL), pp. 1249–1256.

KDD-2009-DonmezCS #learning

Efficiently learning the accuracy of labeling sources for selective sampling (PD, JGC, JGS), pp. 259–268.

KDD-2009-Last #data mining #mining

Improving data mining utility with projective sampling (ML), pp. 487–496.

MLDM-2009-SakaiI #clustering #performance #random

Fast Spectral Clustering with Random Projection and Sampling (TS, AI), pp. 372–384.

SIGIR-2009-CormackC #email #on the

On the relative age of spam and ham training samples for email filtering (GVC, JMMdC), pp. 744–745.

SIGIR-2009-SmuckerAC #evaluation #information retrieval #statistics #testing

Agreement among statistical significance tests for information retrieval evaluation at varying sample sizes (MDS, JA, BC), pp. 630–631.

SIGIR-2009-ThomasS #named

SUSHI: scoring scaled samples for server selection (PT, MS), pp. 419–426.

SIGIR-2009-YangWGH #learning #query #ranking #web

Query sampling for ranking learning in web search (LY, LW, BG, XSH), pp. 754–755.

SAC-2009-JesiMNS #approach

Prestige-based peer sampling service: interdisciplinary approach to secure gossip (GPJ, EM, SKN, MvS), pp. 1209–1213.

SAC-2009-WangCH #learning #multi #music #retrieval

Music retrieval based on a multi-samples selection strategy for support vector machine active learning (TW, GC, PH), pp. 1750–1751.

ASE-2008-DwyerDE #cost analysis #monitoring

Reducing the Cost of Path Property Monitoring Through Sampling (MBD, MD, SGE), pp. 228–237.

ASE-2008-Yom-TovTUH #automation #concurrent #debugging #random #source code

Automatic Debugging of Concurrent Programs through Active Sampling of Low Dimensional Random Projections (EYT, RT, SU, SH), pp. 307–316.

CASE-2008-BrantleyLCC #design #empirical #optimisation #probability

Optimal sampling in design of experiment for simulation-based stochastic optimization (MWB, LHL, CHC, AC), pp. 388–393.

CASE-2008-HooverMR #3d #detection #image #matrix #using

Pose detection of 3-D objects using images sampled on SO(3), spherical harmonics, and wigner-D matrices (RCH, AAM, RGR), pp. 47–52.

CASE-2008-YuanZC #automation

Automatic mixing of highly viscous bio-samples (LY, YFZ, WC), pp. 900–905.

SIGMOD-2008-GemullaL #bound

Sampling time-based sliding windows in bounded space (RG, WL), pp. 379–392.

SIGMOD-2008-LiHYLS #framework #statistics

Sampling cube: a framework for statistical olap over sampling data (XL, JH, ZY, JGL, YS), pp. 779–790.

SIGMOD-2008-PanZW #clustering #composition #dataset #matrix #named #performance #scalability

CRD: fast co-clustering on large datasets utilizing sampling-based matrix decomposition (FP, XZ, WW), pp. 173–184.

VLDB-2008-Bar-YossefG #mining #query

Mining search engine query logs via suggestion sampling (ZBY, MG), pp. 54–65.

VLDB-2008-HadjieleftheriouYKS #query #set #similarity

Hashed samples: selectivity estimators for set similarity selection queries (MH, XY, NK, DS), pp. 201–212.

VLDB-2008-NathG #maintenance #online #random #scalability

Online maintenance of very large random samples on flash storage (SN, PBG), pp. 970–983.

CHI-2008-KapoorH #case study #comparative #experience #modelling #predict

Experience sampling for building predictive user models: a comparative study (AK, EH), pp. 657–666.

ICML-2008-BowlingJBS #evaluation #game studies

Strategy evaluation in extensive games with importance sampling (MHB, MJ, NB, DS), pp. 72–79.

ICML-2008-DasguptaH #learning

Hierarchical sampling for active learning (SD, DH), pp. 208–215.

ICML-2008-DonmezC #learning #optimisation #rank #reduction

Optimizing estimated loss reduction for active sampling in rank learning (PD, JGC), pp. 248–255.

ICML-2008-GaelSTG #infinity #markov

Beam sampling for the infinite hidden Markov model (JVG, YS, YWT, ZG), pp. 1088–1095.

ICML-2008-LazaricRB #learning

Transfer of samples in batch reinforcement learning (AL, MR, AB), pp. 544–551.

ICML-2008-SilverSM #learning

Sample-based learning and search with permanent and transient memories (DS, RSS, MM), pp. 968–975.

ICPR-2008-KuksaHP #detection #kernel #performance

Fast protein homology and fold detection with sparse spatial sample kernels (PPK, PHH, VP), pp. 1–4.

ICPR-2008-LachezeB #image #locality #using

Image sampling for localization using entropy (LL, RB), pp. 1–4.

ICPR-2008-LiuLLJT #graph #probability #representation

Layered shape matching and registration: Stochastic sampling with hierarchical graph representation (XL, LL, HL, HJ, WT), pp. 1–4.

ICPR-2008-SekiH #3d #multi #realtime #using

Real-time 3D tracking using multiple sample points (AS, HH), pp. 1–4.

KDD-2008-ChenW #classification #feature model #metric #named #performance #problem

FAST: a roc-based feature selection metric for small samples and imbalanced data classification problems (XwC, MW), pp. 124–132.

KDD-2008-PorteousNIASW #performance

Fast collapsed gibbs sampling for latent dirichlet allocation (IP, DN, ATI, AUA, PS, MW), pp. 569–577.

KDD-2008-YuJ #kernel #using

Training structural svms with kernels using sampled cuts (CNJY, TJ), pp. 794–802.

SIGIR-2008-Thomas #multi

Generalising multiple capture-recapture to non-uniform sample sizes (PT), pp. 839–840.

SIGIR-2008-YilmazKA #performance

A simple and efficient sampling method for estimating AP and NDCG (EY, EK, JAA), pp. 603–610.

SPLC-2008-CzarneckiSW #feature model #modelling

Sample Spaces and Feature Models: There and Back Again (KC, SS, AW), pp. 22–31.

ISMM-2008-ZhongC #approximate #locality

Sampling-based program locality approximation (YZ, WC), pp. 91–100.

ICST-2008-KodreZR #approach #statistics #testing

Statistical Sampling Based Approach to Alleviate Log Replay Testing (RK, HZ, DJR), pp. 533–536.

ISSTA-2008-QuCR #empirical #testing

Configuration-aware regression testing: an empirical study of sampling and prioritization (XQ, MBC, GR), pp. 75–86.

ASE-2007-YuanCM #array #automation #sequence #testing #user interface

Covering array sampling of input event sequences for automated gui testing (XY, MBC, AMM), pp. 405–408.

CASE-2007-LiW #analysis #approach #reliability

An Importance Sampling Based Approach for Reliability Analysis (FL, TW), pp. 956–961.

CASE-2007-YuanZCC #automation #using

Automatic Mixing of Bio-Samples Using Micro-Channel and Centrifugation (LY, YFZ, WC, MC), pp. 634–639.

DATE-2007-ZhuP #algorithm #graph #probability #random

Random sampling of moment graph: a stochastic Krylov-reduction algorithm (ZZ, JRP), pp. 1502–1507.

ICDAR-2007-Martinez-DiazFFO #on the #verification

On The Effects of Sampling Rate and Interpolation in HMM-Based Dynamic Signature Verification (MMD, JFA, MRF, JOG), pp. 1113–1117.

PODS-2007-GemullaLH #evolution #maintenance #multi

Maintaining bernoulli samples over evolving multisets (RG, WL, PJH), pp. 93–102.

SIGMOD-2007-DasguptaDM #approach #database #random

A random walk approach to sampling hidden databases (AD, GD, HM), pp. 629–640.

SIGMOD-2007-LarsonLZZ #assurance #estimation #quality #using

Cardinality estimation using sample views with quality assurance (PÅL, WL, JZ, PZ), pp. 175–186.

SIGMOD-2007-LarsonLZZ07a #estimation #self

Exploiting self-monitoring sample views for cardinality estimation (PÅL, WL, JZ, PZ), pp. 1073–1075.

FoSSaCS-2007-AbdullaKY #automaton

Sampled Universality of Timed Automata (PAA, PK, WY), pp. 2–16.

TACAS-2007-PandyaKL #abstraction #logic #on the

On Sampling Abstraction of Continuous Time Logic with Durations (PKP, SNK, KL), pp. 246–260.

STOC-2007-DeshpandeV #approximate #reduction

Sampling-based dimension reduction for subspace approximation (AD, KRV), pp. 641–650.

STOC-2007-NissimRS #data analysis

Smooth sensitivity and sampling in private data analysis (KN, SR, AS), pp. 75–84.

ICALP-2007-BlomerN

Sampling Methods for Shortest Vectors, Closest Vectors and Successive Minima (JB, SN), pp. 65–77.

ICALP-2007-IshaiMSW #approximate #multi

Private Multiparty Sampling and Approximation of Vector Combinations (YI, TM, MJS, RNW), pp. 243–254.

ICALP-2007-MotwaniPX

Estimating Sum by Weighted Sampling (RM, RP, YX), pp. 53–64.

HCI-IDU-2007-Berkman #approach #interactive #testing #usability

General Interaction Expertise: An Approach for Sampling in Usability Testing of Consumer Products (AEB), pp. 397–406.

ICML-2007-ChenJ #classification #feature model #set

Minimum reference set based feature selection for small sample classifications (XwC, JCJ), pp. 153–160.

ICML-2007-Shah #bound

Sample compression bounds for decision trees (MS), pp. 799–806.

SIGIR-2007-RowlandsHS #enterprise #evaluation

Workload sampling for enterprise search evaluation (TR, DH, RSS), pp. 887–888.

SIGIR-2007-Soboroff #comparison

A comparison of pooled and sampled relevance judgments (IS), pp. 785–786.

SIGIR-2007-ThomasH

Evaluating sampling methods for uncooperative collections (PT, DH), pp. 503–510.

OOPSLA-2007-BuytaertGHAEB #compilation #using

Using hpm-sampling to drive dynamic compilation (DB, AG, MH, MA, LE, KDB), pp. 553–568.

SAC-2007-AppelPSTT #clustering

Biased box sampling — a density-biased sampling for clustering (APA, AAP, EPMdS, AJMT, CTJ), pp. 445–446.

SAC-2007-SchusterS #documentation #estimation #natural language #query #random #web

NL sampler: random sampling of web documents based on natural language with query hit estimation (DS, AS), pp. 812–818.

SAC-2007-ZhangZZMY #algorithm #random #streaming

A priority random sampling algorithm for time-based sliding windows over weighted streaming data (LZ, ZL, YQZ, YM, ZY), pp. 453–456.

ESEC-FSE-2007-SankaranarayananCJI #constraints #feedback #generative #monte carlo #using

State space exploration using feedback constraint generation and Monte-Carlo sampling (SS, RMC, GJ, FI), pp. 321–330.

DAC-2006-KanjJN #analysis #design

Mixture importance sampling and its application to the analysis of SRAM designs in the presence of rare failure events (RK, RVJ, SRN), pp. 69–72.

DATE-2006-MajidzadehS #design #higher-order #novel

Arbitrary design of high order noise transfer function for a novel class of reduced-sample-rate sigma-delta-pipeline ADCs (VM, OS), pp. 138–143.

DATE-2006-YavariSR06a

Double-sampling single-loop sigma-delta modulator topologies for broadband applications (MY, OS, ÁRV), pp. 399–404.

SIGMOD-2006-KleinGRL #named #query

Derby/S: a DBMS for sample-based query answering (AK, RG, PR, WL), pp. 757–759.

VLDB-2006-Aggarwal #evolution #on the

On Biased Reservoir Sampling in the Presence of Stream Evolution (CCA), pp. 607–618.

VLDB-2006-GemullaLH #dataset #evolution #maintenance

A Dip in the Reservoir: Maintaining Sample Synopses of Evolving Datasets (RG, WL, PJH), pp. 595–606.

STOC-2006-DubrovI #complexity #on the #performance

On the randomness complexity of efficient sampling (BD, YI), pp. 711–720.

STOC-2006-FischerRV #adaptation #convergence #performance

Fast convergence to Wardrop equilibria by adaptive sampling methods (SF, HR, BV), pp. 653–662.

STOC-2006-LeviRS #algorithm #modelling #probability

Provably near-optimal sampling-based algorithms for Stochastic inventory control models (RL, RR, DBS), pp. 739–748.

STOC-2006-Szegedy

The DLT priority sampling is essentially optimal (MS), pp. 150–158.

CHI-2006-IachelloTAHS #experience #privacy #prototype #ubiquitous

Prototyping and sampling experience to evaluate ubiquitous computing privacy in the real world (GI, KNT, GDA, GRH, MMS), pp. 1009–1018.

ICEIS-DISI-2006-LongboZMYY #algorithm #data type #random

Random Sampling Algorithms for Landmark Windows over Data Streams (LZ, ZL, YM, WY, JY), pp. 103–107.

ICML-2006-HertzBW #classification #kernel #learning

Learning a kernel function for classification with small training samples (TH, ABH, DW), pp. 401–408.

ICML-2006-VeeramachaneniOA #detection

Active sampling for detecting irrelevant features (SV, EO, PA), pp. 961–968.

ICPR-v1-2006-HuaWCW #algorithm

A Pixel-wise Object Tracking Algorithm with Target and Background Sample (CH, HW, QC, TW), pp. 739–742.

ICPR-v1-2006-IshiyamaIS

A Compact Model of Human Postures Extracting Common Motion from Individual Samples (RI, HI, SS), pp. 187–190.

ICPR-v1-2006-ShanLC #image #recognition #robust

Face Recognition Robust to Head Pose from One Sample Image (TS, BCL, SC), pp. 515–518.

ICPR-v2-2006-ChengW #feedback #image #multi #retrieval

Multi-View Sampling for Relevance Feedback in Image Retrieval (JC, KW), pp. 881–884.

ICPR-v2-2006-FangQ #classification

Car/Non-Car Classification in an Informative Sample Subspace (JF, GQ), pp. 962–965.

ICPR-v2-2006-ZhengYYW #classification #effectiveness #image #problem

Effective classification image space which can solve small sample size problem (YJZ, JYY, JY, XW), pp. 861–864.

ICPR-v3-2006-BalciAF

Subpixel Alignment of MRI Data Under Cartesian and Log-Polar Sampling (MB, MA, HF), pp. 607–610.

ICPR-v3-2006-KierA #classification #multi #predict

Predicting the benefit of sample size extension in multiclass k-NN classification (CK, TA), pp. 332–335.

ICPR-v3-2006-KostlerPRH #adaptation

Adaptive variational sinogram interpolation of sparsely sampled CT data (HK, MP, UR, JH), pp. 778–781.

ICPR-v3-2006-TanakaFKI #theorem

A Theoretical and Experimental Consideration on Interference in Resolutions between Sampling Theorem and OK-Quantization Theory (YT, TF, HK, TI), pp. 869–872.

KDD-2006-AbeZL06a #detection

Outlier detection by sampling with accuracy guarantees (MW, CJ), pp. 767–772.

KDD-2006-FanD #bias #classification #framework #performance #testing

Reverse testing: an efficient framework to select amongst classifiers under sample selection bias (WF, ID), pp. 147–156.

KDD-2006-LeskovecF #graph #scalability

Sampling from large graphs (JL, CF), pp. 631–636.

KDD-2006-YeW #analysis

Regularized discriminant analysis for high dimensional, low sample size data (JY, TW), pp. 454–463.

SIGIR-2006-AzzopardiBC #adaptation #distributed #information retrieval

Adaptive query-based sampling for distributed IR (LA, MB, FC), pp. 605–606.

SIGIR-2006-CaverleeLB #approach #distributed #query

Distributed query sampling: a quality-conscious approach (JC, LL, JB), pp. 340–347.

OOPSLA-2006-SahavechaphanC #mining #named

XSnippet: mining For sample code (NS, KTC), pp. 413–430.

SAC-2006-PechenizkiyPT #feature model #learning #reduction

The impact of sample reduction on PCA-based feature extraction for supervised learning (MP, SP, AT), pp. 553–558.

ICSE-2006-Sindhgatta #information retrieval #source code #using

Using an information retrieval system to retrieve source code samples (RS), pp. 905–908.

CASE-2005-MeldrumHFSMRPMCDW #analysis

Sample preparation in glass capillaries for high-throughput biochemical analyses (DRM, MH, CHF, MSS, SKM, TTHR, WHP, SEM, DLC, DAD, PJW), pp. 7–12.

DAC-2005-Li #analysis #grid #performance #power management #simulation

Power grid simulation via efficient sampling-based sensitivity analysis and hierarchical symbolic relaxation (PL), pp. 664–669.

DAC-2005-Vasudevan #simulation

Simulation of the effects of timing jitter in track-and-hold and sample-and-hold circuits (VV), pp. 397–402.

DATE-2005-MartensG #integration #orthogonal #polynomial #simulation #using

Time-Domain Simulation of Sampled Weakly Nonlinear Systems Using Analytical Integration and Orthogonal Polynomial Series (EM, GGEG), pp. 120–125.

DATE-2005-ScholiveBRFR #generative #testing

Mutation Sampling Technique for the Generation of Structural Test Data (MS, VB, CR, MLF, BR), pp. 1022–1023.

ICDAR-2005-LiwickiB #database #recognition

Enhancing Training Data for Handwriting Recognition of Whiteboard Notes with Samples from a Different Database (ML, HB), pp. 550–554.

SIGMOD-2005-JohnsonMR #algorithm

Sampling Algorithms in a Stream Operator (TJ, SM, IR), pp. 1–12.

VLDB-2005-CormodeMR #data type #mining

Summarizing and Mining Inverse Distributions on Data Streams via Dynamic Inverse Sampling (GC, SM, IR), pp. 25–36.

STOC-2005-AchlioptasCKM #bias #graph #on the

On the bias of traceroute sampling: or, power-law degree distributions in regular graphs (DA, AC, DK, CM), pp. 694–703.

ICALP-2005-RadhakrishnanRS #fourier #on the #power of #problem #random

On the Power of Random Bases in Fourier Sampling: Hidden Subgroup Problem in the Heisenberg Group (JR, MR, PS), pp. 1399–1411.

CIKM-2005-AfratiLL #adaptation #query #using #web

Answering aggregation queries on hierarchical web sites using adaptive sampling (FNA, PVL, CL), pp. 237–238.

ICML-2005-LavioletteM #bound #classification

PAC-Bayes risk bounds for sample-compressed Gibbs classifiers (FL, MM), pp. 481–488.

ICML-2005-LeiteB #classification #performance #predict

Predicting relative performance of classifiers from samples (RL, PB), pp. 497–503.

ICML-2005-SinghPGBB #analysis #learning

Active learning for sampling in time-series experiments with application to gene expression analysis (RS, NP, DKG, BB, ZBJ), pp. 832–839.

ICML-2005-SzepesvariM #bound #finite

Finite time bounds for sampling based fitted value iteration (CS, RM), pp. 880–887.

ICML-2005-WangLBS #online #optimisation

Bayesian sparse sampling for on-line reward optimization (TW, DJL, MHB, DS), pp. 956–963.

KDD-2005-Scholz #mining

Sampling-based sequential subgroup mining (MS), pp. 265–274.

KDD-2005-Yu #ranking #retrieval

SVM selective sampling for ranking with application to data retrieval (HY), pp. 354–363.

SIGIR-2005-TrieschniggK #approach #detection #scalability #topic

Scalable hierarchical topic detection: exploring a sample based approach (DT, WK), pp. 655–656.

POPL-2005-ParkPT #probability

A probabilistic language based upon sampling functions (SP, FP, ST), pp. 171–182.

LCTES-2005-XuL

A sample-based cache mapping scheme (RX, ZL), pp. 166–174.

PPoPP-2005-CongHHP #data mining #framework #mining #parallel

A sampling-based framework for parallel data mining (SC, JH, JH, DAP), pp. 255–265.

PODS-2004-HershbergerS #adaptation #data type #geometry #problem

Adaptive Sampling for Geometric Problems over Data Streams (JH, SS), pp. 252–262.

SIGMOD-2004-ChaudhuriDS #effectiveness #estimation #statistics

Effective Use of Block-Level Sampling in Statistics Estimation (SC, GD, US), pp. 287–298.

SIGMOD-2004-GryzGLZ #database #query

Query Sampling in DB2 Universal Database (JG, JG, LL, CZ), pp. 839–843.

SIGMOD-2004-HaasK #database

A Bi-Level Bernoulli Scheme for Database Sampling (PJH, CK), pp. 275–286.

SIGMOD-2004-IpeirotisG #database #using

When one Sample is not Enough: Improving Text Database Selection Using Shrinkage (PGI, LG), pp. 767–778.

SIGMOD-2004-JermainePA #maintenance #online #random #scalability

Online Maintenance of Very Large Random Samples (CJ, AP, SA), pp. 299–310.

STOC-2004-GuptaPRS #algorithm #approximate #optimisation #probability

Boosted sampling: approximation algorithms for stochastic optimization (AG, MP, RR, AS), pp. 417–426.

ICALP-2004-CzumajS #approximate #clustering #random

Sublinear-Time Approximation for Clustering Via Random Sampling (AC, CS), pp. 396–407.

ICEIS-v1-2004-CortesO #quality #relational

Relational Sampling for Data Quality Auditing and Decision Support (BC, JNO), pp. 376–382.

ICML-2004-Zadrozny #bias #classification #learning

Learning and evaluating classifiers under sample selection bias (BZ).

ICPR-v1-2004-ChenL #image #invariant #recognition

Illumination and Expression Invariant Face Recognition with One Sample Image (SC, BCL), pp. 300–303.

ICPR-v2-2004-FangQ #detection #learning

Learning Sample Subspace with Application to Face Detection (JF, GQ), pp. 423–426.

ICPR-v2-2004-WashizawaY #classification #kernel #pattern matching #pattern recognition #recognition

Kernel Sample Space Projection Classifier for Pattern Recognition (YW, YY), pp. 435–438.

ICPR-v3-2004-BenoitF #kernel

Steerable Kernels for Arbitrarily-Sampled Spaces (SB, FPF), pp. 578–581.

ICPR-v3-2004-ChenYC #distance #multi #recognition

Inter-Subspace Distance: A New Method for Face Recognition with Multiple Samples (JHC, SLY, CSC), pp. 140–143.

ICPR-v3-2004-JuszczakD

Selective Sampling Based on the Variation in Label Assignments (PJ, RPWD), pp. 375–378.

ICPR-v3-2004-KuhlKWK #classification #using

Training of Classifiers Using Virtual Samples Only (AK, LK, CW, UK), pp. 418–421.

ICPR-v3-2004-SprevakAW #assessment #classification

A Non-Random Data Sampling Method for Classification Model Assessment (DS, FA, HW), pp. 406–409.

ICPR-v4-2004-BradleyL #estimation #using

Sample Size Estimation using the Receiver Operating Characteristic Curve (APB, IDL), pp. 428–431.

ICPR-v4-2004-FrancoLM #approach #feedback

A New Approach for Relevance Feedback Through Positive and Negative Samples (AF, AL, DM), pp. 905–908.

KDD-2004-JiangPRTZ #array #clustering #mining

Mining coherent gene clusters from gene-sample-time microarray data (DJ, JP, MR, CT, AZ), pp. 430–439.

SIGIR-2004-FanL #classification #semantics #video

Semantic video classification by integrating unlabeled samples for classifier training (JF, HL), pp. 592–593.

SAC-2004-TrutaFB #metric

Disclosure risk measures for the sampling disclosure control method (TMT, FF, DCBJ), pp. 301–306.

ISMM-2004-JumpBM

Dynamic object sampling for pretenuring (MJ, SMB, KSM), pp. 152–162.

DATE-2003-VanasscheGS #analysis #detection #domain model #modelling

Time-Varying, Frequency-Domain Modeling and Analysis of Phase-Locked Loops with Sampling Phase-Frequency Detectors (PV, GGEG, WMCS), pp. 10238–10243.

SIGMOD-2003-BabcockCD #approximate #query

Dynamic Sample Selection for Approximate Query Processing (BB, SC, GD), pp. 539–550.

VLDB-2003-Jermaine #approximate #estimation #robust

Robust Estimation With Sampling and Approximate Pre-Aggregation (CJ), pp. 886–897.

IWPC-2003-ChanHMY #execution #object-oriented #scalability #visualisation

Scaling an Object-Oriented System Execution Visualizer through Sampling (AC, RH, GCM, ATTY), pp. 237–244.

PLDI-2003-LiblitAZJ #debugging

Bug isolation via remote program sampling (BL, AA, AXZ, MIJ), pp. 141–154.

STOC-2003-Bar-Yossef #bound

Sampling lower bounds via information theory (ZBY), pp. 335–344.

STOC-2003-ItohTT #independence #on the #permutation #strict

On the sample size of k-restricted min-wise independent permutations and other k-wise distributions (TI, YT, JT), pp. 710–719.

ICALP-2003-PoulalhonS

Optimal Coding and Sampling of Triangulations (DP, GS), pp. 1080–1094.

ECIR-2003-XuYTXW #classification #using

Representative Sampling for Text Classification Using Support Vector Machines (ZX, KY, VT, XX, JW), pp. 393–407.

ICML-2003-Strens #optimisation

Evolutionary MCMC Sampling and Optimization in Discrete Spaces (MJAS), pp. 736–743.

KDD-2003-DuMouchelA #design

Applications of sampling and fractional factorial designs to model-free data squashing (WD, DKA), pp. 511–516.

KDD-2003-TsamardinosAS #markov #performance

Time and sample efficient discovery of Markov blankets and direct causal relations (IT, CFA, ARS), pp. 673–678.

CGO-2003-ChenHC #hardware #monitoring #performance #using

Dynamic Trace Selection Using Performance Monitoring Hardware Sampling (HC, WCH, DyC), pp. 79–90.

SOSP-2003-ManiatisRRBGM

Preserving peer replicas by rate-limited sampled voting (PM, DSHR, MR, MB, TJG, YM), pp. 44–59.

SIGMOD-2002-Aggarwal #estimation #framework #nearest neighbour #reduction

Hierarchical subspace sampling: a unified framework for high dimensional data reduction, selectivity estimation and nearest neighbor search (CCA), pp. 452–463.

VLDB-2002-ChoN #detection #effectiveness #using

Effective Change Detection Using Sampling (JC, AN), pp. 514–525.

VLDB-2002-IpeirotisG #database #distributed #web

Distributed Search over the Hidden Web: Hierarchical Database Sampling and Selection (PGI, LG), pp. 394–405.

STOC-2002-AlonVKK #approximate #problem #random

Random sampling and approximation of MAX-CSP problems (NA, WFdlV, RK, MK), pp. 232–239.

STOC-2002-GilbertGIMS #fourier

Near-optimal sparse fourier representations via sampling (ACG, SG, PI, SM, MS), pp. 152–161.

STOC-2002-KargerL #graph #random

Random sampling in residual graphs (DRK, MSL), pp. 63–66.

ICALP-2002-DuchonFLS #random

Random Sampling from Boltzmann Principles (PD, PF, GL, GS), pp. 501–513.

CIKM-2002-NanopoulosMT #algorithm #effectiveness #performance

An efficient and effective algorithm for density biased sampling (AN, YM, YT), pp. 398–404.

ICML-2002-LiuMY #feature model

Feature Selection with Selective Sampling (HL, HM, LY), pp. 395–402.

ICML-2002-StrensBE #markov #monte carlo #optimisation #using

Markov Chain Monte Carlo Sampling using Direct Search Optimization (MJAS, MB, NE), pp. 602–609.

ICPR-v1-2002-YuLC #multi #synthesis

Multiresolution Block Sampling-Based Method for Texture Synthesis (YY, JL, CWC), pp. 239–242.

ICPR-v2-2002-LiZ #algorithm #visual notation

Visual Contour Tracking Based on Sequential Importance Sampling/Resampling Algorithm (PL, TZ), pp. 564–568.

ICPR-v3-2002-HuangLLM #problem

Solving the Small Sample Size Problem of LDA (RH, QL, HL, SM), pp. 29–32.

ICPR-v3-2002-LiY #clustering #normalisation

Normalized Sampling for Color Clustering in Medical Diagnosis (CHL, PCY), pp. 819–822.

KDD-2002-ChenHS #algorithm

A new two-phase sampling based algorithm for discovering association rules (BC, PJH, PS), pp. 462–468.

SIGIR-2002-SiC #using

Using sampled data and regression to merge search engine results (LS, JPC), pp. 19–26.

SAC-2002-DolinBR #co-evolution #distributed #effectiveness

Co-evolving an effective fitness sample: experiments in symbolic regression and distributed robot control (BD, FHBI, EGR), pp. 553–559.

CAV-2002-YounesS #probability #using #verification

Probabilistic Verification of Discrete Event Systems Using Acceptance Sampling (HLSY, RGS), pp. 223–235.

TestCom-2002-Veciana-NoguesCDS #metric #verification

Verifying IP Meters from Sampled Measurements (CVN, ACA, JDP, JSP), pp. 39–54.

ICDAR-2001-BarakatB #classification #geometry

Training with Positive and Negative Data Samples: Effects on a Classifier for Hand-Drawn Geometric Shapes (HB, DB), pp. 1017–1021.

VLDB-2001-Gibbons #query

Distinct Sampling for Highly-Accurate Answers to Distinct Values Queries and Event Reports (PBG), pp. 541–550.

STOC-2001-Bar-YossefKS #algorithm #bound

Sampling algorithms: lower bounds and applications (ZBY, RK, DS), pp. 266–275.

ICML-2001-RoyM #estimation #fault #learning #reduction #towards

Toward Optimal Active Learning through Sampling Estimation of Error Reduction (NR, AM), pp. 441–448.

SAC-2001-BadgerK #taxonomy

Picking fruit from the tree of life: comments on taxonomic sampling and quartet methods (JHB, PEK), pp. 61–67.

DAC-2000-LuJCF #performance #using

Efficient variable ordering using aBDD based sampling (YL, JJ, EMC, MF), pp. 687–692.

DATE-2000-JantschB

Composite Signal Flow: A Computational Model Combining Events, Sampled Streams, and Vectors (AJ, PB), pp. 154–160.

PODS-2000-Lynch #adaptation #analysis

Analysis and Application of Adaptive Sampling (JFL), pp. 260–267.

SIGMOD-2000-AcharyaGP #approximate #query

Congressional Samples for Approximate Answering of Group-By Queries (SA, PBG, VP), pp. 487–498.

SIGMOD-2000-PalmerF #clustering #data mining #mining

Density Biased Sampling: An Improved Method for Data Mining and Clustering (CRP, CF), pp. 82–92.

SIGMOD-2000-WaasG #cost analysis #execution #query

Counting, Enumerating, and Sampling of Execution Plans in a Cost-Based Query Optimizer (FW, CAGL), pp. 499–509.

VLDB-2000-GantiLR #approximate #named #query #self

ICICLES: Self-Tuning Samples for Approximate Query Answering (VG, MLL, RR), pp. 176–187.

STOC-2000-Grover #agile #quantum

Rapid sampling though quantum computing (LKG), pp. 618–626.

CIKM-2000-MakawitaTL #database #using

Sampling from Databases Using B+-Trees (DPM, KLT, HL), pp. 158–164.

ICPR-v2-2000-MitaniH #classification #design #nearest neighbour

Classifier Design Based on the Use of Nearest Neighbor Samples (YM, YH), pp. 2769–2772.

ICPR-v2-2000-MiyamotoHM #classification #design #polynomial

Use of Bootstrap Samples in Quadratic Classifier Design (TM, YH, YM), pp. 2789–2792.

ICPR-v2-2000-Schulerud #analysis #bias #fault #feature model #linear

Bias of Error Rates in Linear Discriminant Analysis Caused by Feature Selection and Sample Size (HS), pp. 2372–2377.

ICPR-v3-2000-ThiemH #design

Biology-Inspired Design of Digital Gabor Filters upon a Hexagonal Sampling Scheme (JT, GH), pp. 3449–3452.

KDD-2000-SchefferW #algorithm

A sequential sampling algorithm for a general class of utility criteria (TS, SW), pp. 330–334.

ASPLOS-2000-BurrowsELVWWW #flexibility #performance

Efficient and Flexible Value Sampling (MB, ÚE, STL, MTV, CAW, KW, WEW), pp. 160–167.

ISMM-2000-AgesenG #performance

Efficient Object Sampling via Weak References (OA, AG), pp. 121–126.

ICDAR-1999-KhanH #recognition #using

Recognition of Real-Life Character Samples using a Structural Variation and Degradation Model (NAK, HH), pp. 225–228.

SIGMOD-1999-ChaudhuriMN #on the #random

On Random Sampling over Joins (SC, RM, VRN), pp. 263–274.

SIGMOD-1999-MankuRL #dataset #online #order #performance #random #scalability #statistics

Random Sampling Techniques for Space Efficient Online Computation of Order Statistics of Large Datasets (GSM, SR, BGL), pp. 251–262.

STOC-1999-HalesH #fourier #quantum

Quantum Fourier Sampling Simplified (LH, SH), pp. 330–338.

STOC-1999-PonzioRV #communication #complexity #pointer

The Communication Complexity of Pointer Chasing: Applications of Entropy and Sampling (SP, JR, SV), pp. 602–611.

STOC-1999-Schaeffer #random #scalability

Random Sampling of Large Planar Maps and Convex Polyhedra (GS), pp. 760–769.

STOC-1999-Servedio #complexity #learning

Computational Sample Complexity and Attribute-Efficient Learning (RAS), pp. 701–710.

KDD-1999-ProvostJO #performance

Efficient Progressive Sampling (FJP, DJ, TO), pp. 23–32.

MLDM-1999-ReczkoKMGO #estimation #image #network

Neural Networks in MR Image Estimation from Sparsely Sampled Scans (MR, DAK, VM, DGD, DvO), pp. 75–86.

SIGIR-1999-CormackLP #precise #random

Estimating Precision by Random Sampling (poster abstract) (GVC, OL, CRP), pp. 273–274.

SIGMOD-1998-ChaudhuriMN #how #question #random

Random Sampling for Histogram Construction: How much is enough? (SC, RM, VRN), pp. 436–447.

SIGMOD-1998-GibbonsM #approximate #query #statistics #summary

New Sampling-Based Summary Statistics for Improving Approximate Query Answers (PBG, YM), pp. 331–342.

STOC-1998-Huber #approximate

Exact Sampling and Approximate Counting Techniques (MH), pp. 31–40.

ICALP-1998-DyerG #algorithm #polynomial

A Genuinely Polynomial-Time Algorithms for Sampling Two-Rowed Contingency Tables (MED, CSG), pp. 339–350.

ICALP-1998-MartinezR

Optimal Sampling Strategies in Quicksort (CM, SR), pp. 327–338.

ICPR-1998-Duin #analysis #problem #relational #scalability

Relational discriminant analysis and its large sample size problem (RPWD), pp. 445–449.

ICPR-1998-MahlmeisterSS #image

Sample-guided progressive image coding (UM, MS, GS), pp. 1257–1259.

ICPR-1998-PetersS #realtime

A real-time variable sampling technique: DIEM (MWP, AS), pp. 316–321.

KDD-1998-OliverRGBBW

Analysing Rock Samples for the Mars Lander (JJO, TR, PG, WLB, RAB, SRW), pp. 299–303.

SAC-1998-LiWP #modelling #process #simulation

Modelling and simulation of fractional ARIMA processes based on importance sampling (JSL, AW, RPZ), pp. 453–455.

HPCA-1998-VengroffG #branch #estimation #performance #predict #re-engineering

Partial Sampling with Reverse State Reconstruction: A New Technique for Branch Predictor Performance Estimation (DEV, GRG), pp. 342–351.

ICDAR-1997-NakagawaHYSHA #database #online #sequence

On-line Handwritten Character Pattern Database Sampled in a Sequence of Sentences without any Writing Instructions (MN, TH, YY, SiS, LH, KA), pp. 376–381.

ICDAR-1997-Yamada #feature model #recognition

Non-uniformly Sampled Feature Extraction Method for Kanji Character Recognition (KY), pp. 200–205.

ITiCSE-WGR-1997-JoyceKGKKLLSW #design #guidelines #recommendation #repository

Developing laboratories for the SIGCSE computing laboratory repository: guidelines, recommendations, and sample labs (report of the ITiCSE 1997 working group on designing laboratory materials for computing courses) (DTJ, DK, JGP, EBK, WK, CL, KL, ES, RAW), pp. 1–12.

STOC-1997-Fill #algorithm #markov

An Interruptible Algorithm for Perfect Sampling via Markov Chains (JAF), pp. 688–695.

STOC-1997-KannanV

Sampling Lattice Points (RK, SV), pp. 696–700.

STOC-1997-Karger #graph #random #using

Using Random Sampling to Find Maximum Flows in Uncapacitated Undirected Graphs (DRK), pp. 240–249.

SIGMOD-1996-GangulyGMS #estimation

Bifocal Sampling for Skew-Resistant Join Size Estimation (SG, PBG, YM, AS), pp. 271–281.

VLDB-1996-Toivonen #database #scalability

Sampling Large Databases for Association Rules (HT), pp. 134–145.

STOC-1996-Zuckerman

Randomness-Optimal Sampling, Extractors, and Constructive Leader Election (DZ), pp. 286–295.

ICALP-1996-HenzingerT #algorithm #graph

Improved Sampling with Applications to Dynamic Graph Algorithms (MRH, MT), pp. 290–299.

ICPR-1996-ChenJ #behaviour #network #on the

On the small sample behavior of the class-sensitive neural network (CHC, AJ), pp. 209–213.

ICPR-1996-GriffinKWM

Techniques for the interpretation of thermal paint coated samples (AG, JK, TW, JM), pp. 959–963.

ICPR-1996-KimK #multi #recognition

Multi-font and multi-size character recognition based on the sampling and quantization of an unwrapped contour (MKK, YBK), pp. 170–174.

ICPR-1996-SkurichinaD #classification

Stabilizing classifiers for very small sample sizes (MS, RPWD), pp. 891–896.

ICPR-1996-Young #analysis #image

Sampling density for image analysis (ITY), pp. 840–843.

KDD-1996-JohnL #data mining #mining

Static Versus Dynamic Sampling for Data Mining (GHJ, PL), pp. 367–370.

SAC-1996-Duben #statistics #using

Conformational statistics of the nitrogen linkage in glycopeptides using umbrella sampling (AJD), pp. 38–43.

ICDAR-v1-1995-LoprestiZNS #recognition

Spatial sampling effects in optical character recognition (DPL, JZ, GN, PS), pp. 309–314.

ICDAR-v1-1995-Yamada #recognition

Optimal sampling intervals for Gabor features and printed Japanese character recognition (KY), pp. 150–153.

VLDB-1995-HaasNSS #estimation

Sampling-Based Estimation of the Number of Distinct Values of an Attribute (PJH, JFN, SS, LS), pp. 311–322.

CIKM-1995-IkejiF #adaptation #query #using

Computation of Partial Query Results Using An Adaptive Stratified Sampling Technique (ACI, FF), pp. 145–149.

ICML-1995-DaganE #classification #probability

Committee-Based Sampling For Training Probabilistic Classifiers (ID, SPE), pp. 150–157.

ICML-1995-Niyogi #complexity #learning

Free to Choose: Investigating the Sample Complexity of Active Learning of Real Valued Functions (PN), pp. 405–412.

SAC-1995-Duben #modelling #statistics #using

Conformational statistics of models for serine- and threonine-linked glycopeptides using umbrella sampling (AJD), pp. 108–112.

EDAC-1994-DumasGLP #effectiveness #fault

Effectiveness of a Variable Sampling Time Strategy for Delay Fault Diagnosis (DD, PG, CL, SP), pp. 518–523.

PODS-1994-HaasNS #estimation #on the

On the Relative Cost of Sampling for Join Selectivity Estimation (PJH, JFN, ANS), pp. 14–24.

PODS-1994-KivinenM #information management #power of

The Power of Sampling in Knowledge Discovery (JK, HM), pp. 77–85.

STOC-1994-Karger #design #network #problem #random

Random sampling in cut, flow, and network design problems (DRK), pp. 648–657.

ICML-1994-CravenS #network #query #using

Using Sampling and Queries to Extract Rules from Trained Neural Networks (MC, JWS), pp. 37–45.

ICML-1994-LewisC #learning #nondeterminism

Heterogenous Uncertainty Sampling for Supervised Learning (DDL, JC), pp. 148–156.

ICML-1994-Skalak #algorithm #feature model #prototype #random

Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms (DBS), pp. 293–301.

ICML-1994-WeissI

Small Sample Decision tree Pruning (SMW, NI), pp. 335–342.

ICDAR-1993-CaesarGM93a #adaptation #classification #scalability #set

Utilization of large disordered sample sets for classifier adaptation in complex domains (TC, JMG, EM), pp. 790–793.

ICDAR-1993-TakeshitaNK #bias #distance #on the

On the bias of Mahalanobis distance due to limited sample size effect (TT, SN, FK), pp. 171–174.

CSM-1993-Talbert #assurance #quality

Representative Sampling Within Software Quality Assurance (NBT), pp. 174–179.

STOC-1993-KollerM #constraints

Constructing small sample spaces satisfying given constraints (DK, NM), pp. 268–277.

INTERCHI-1993-Weiler #tool support #usability

Software for the usability lab: a sampling of current tools (PW), pp. 57–60.

SAC-1993-Sabharwal #approach #parametricity

An Intelligent Approach to Discrete Sampling of Parametric Curves (CLS), pp. 397–401.

FSE-1993-PodgurskiY #analysis #clustering #testing

Partition testing, stratified sampling, and cluster analysis (AP, CY), pp. 169–181.

SIGMOD-1992-HaasS #estimation #query

Sequential Sampling Procedures for Query Size Estimation (PJH, ANS), pp. 341–350.

VLDB-1992-Antoshenkov #pseudo #random

Random Sampling from Pseudo-Ranked B+ Trees (GA), pp. 375–382.

STOC-1992-Ben-David #detection #finite #question

Can Finite Samples Detect Singularities of Real-Valued Functions? (SBD), pp. 390–399.

STOC-1992-Schulman

Sample Spaces Uniform on Neighborhoods (LJS), pp. 17–25.

ICSE-1992-PodgurskiP #automation #behaviour #component #retrieval #reuse

Behavior Sampling: A Technique for Automated Retrieval of Reusable Components (AP, LP), pp. 349–360.

HT-1991-EganLKLRLL #hypermedia #library

Hypertext for the Electronic Library? CORE Sample Results (DEE, ML, RDK, CCL, JRR, MLL, TKL), pp. 299–312.

STOC-1991-ApplegateK #integration

Sampling and Integration of Near Log-Concave functions (DA, RK), pp. 156–163.

CHI-1991-MorchG #concept #named

JANUS: basic concepts and sample dialog (AIM, AG), pp. 457–458.

TAV-1991-Podgurski #algorithm #reliability

Reliability, Sampling, and Algorithmic Randomness (AP), pp. 11–20.

PODS-1990-LiptonN #adaptation #estimation #query

Query Size Estimation by Adaptive Sampling (RJL, JFN), pp. 40–46.

SIGMOD-1990-LiptonNS #adaptation #estimation

Practical Selectivity Estimation through Adaptive Sampling (RJL, JFN, DAS), pp. 1–11.

SIGMOD-1990-OlkenRX #random

Random Sampling from Hash Files (FO, DR, PX), pp. 375–386.

STOC-1990-Vishkin #pattern matching #performance

Deterministic Sampling-A New Technique for Fast Pattern Matching (UV), pp. 170–180.

VLDB-1989-OlkenR #random

Random Sampling from B+ Trees (FO, DR), pp. 269–277.

STOC-1989-ReifS #geometry #named #random

Polling: A New Randomized Sampling Technique for Computational Geometry (JHR, SS), pp. 394–404.

VDME-1988-JagerGK #functional #named

SAMPLE — A Functional Language (MJ, MG, SK), pp. 202–217.

VLDB-1986-OlkenR #database #random #relational

Simple Random Sampling from Relational Databases (FO, DR), pp. 160–169.

STOC-1986-Clarkson #geometry #random

Further Applications of Random Sampling to Computational Geometry (KLC), pp. 414–423.

ICALP-1984-Willard #algorithm #difference #problem #retrieval

Sampling Algorithms for Differential Batch Retrieval Problems (Extended Abstract) (DEW), pp. 514–526.

DAC-1973-DoonerVL #design #interactive #process

An interactive graphic and process controlled system for composing and sampling loom constrained designs (NPD, PV, JRL), pp. 247–252.