BibSLEIGH
BibSLEIGH corpus
BibSLEIGH tags
BibSLEIGH bundles
BibSLEIGH people
EDIT!
CC-BY
Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
email twitter
monte carlo
Google monte carlo

Tag #monte carlo

183 papers:

AIIDEAIIDE-2019-YangO #game studies #realtime
Guiding Monte Carlo Tree Search by Scripts in Real-Time Strategy Games (ZY, SO), pp. 100–107.
CoGCoG-2019-ChoeK #game studies
Enhancing Monte Carlo Tree Search for Playing Hearthstone (JSBC, JKK), pp. 1–7.
CoGCoG-2019-GreenwoodA #game studies
Monte Carlo Strategies for Exploiting Fairness in N-player Ultimatum Games (GWG, DA), pp. 1–7.
CoGCoG-2019-KantharajuOG #recognition #scalability
Scaling up CCG-Based Plan Recognition via Monte-Carlo Tree Search (PK, SO, CWG), pp. 1–8.
CoGCoG-2019-KiarostamiDMRG #multi
Multi-Agent non-Overlapping Pathfinding with Monte-Carlo Tree Search (MSK, MRD, SKM, DR, SG), pp. 1–4.
CoGCoG-2019-SironiW #parametricity
Comparing Randomization Strategies for Search-Control Parameters in Monte-Carlo Tree Search (CFS, MHMW), pp. 1–8.
ICMLICML-2019-ChenBBGGMO #markov
Stein Point Markov Chain Monte Carlo (WYC, AB, FXB, JG, MAG, LWM, CJO), pp. 1011–1021.
ICMLICML-2019-ChoromanskiRCW #orthogonal
Unifying Orthogonal Monte Carlo Methods (KC, MR, WC, AW), pp. 1203–1212.
ICMLICML-2019-GolinskiWR #integration
Amortized Monte Carlo Integration (AG, FW, TR), pp. 2309–2318.
ICMLICML-2019-NguyenSR #analysis #optimisation
Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization (THN, US, GR), pp. 4810–4819.
ICMLICML-2019-PolianskiiP #approach #bound #classification #geometry #integration
Voronoi Boundary Classification: A High-Dimensional Geometric Approach via Weighted Monte Carlo Integration (VP, FTP), pp. 5162–5170.
ICMLICML-2019-ShestopaloffD
Replica Conditional Sequential Monte Carlo (AS, AD), pp. 5749–5757.
ICMLICML-2019-ZhangZT #adaptation #multi #testing
Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits (MJZ, JZ, DT), pp. 7512–7522.
ASPLOSASPLOS-2019-BanerjeeKI #algorithm #markov #modelling #probability
AcMC 2 : Accelerating Markov Chain Monte Carlo Algorithms for Probabilistic Models (SSB, ZTK, RKI), pp. 515–528.
SEFMSEFM-2018-LuckowPV #source code
Monte Carlo Tree Search for Finding Costly Paths in Programs (KSL, CSP, WV), pp. 123–138.
AIIDEAIIDE-2018-HornMSC #approach #automation
A Monte Carlo Approach to Skill-Based Automated Playtesting (BH, JAM, GS, SC), pp. 166–172.
CoGCIG-2018-GeddaLB #game studies
Monte Carlo Methods for the Game Kingdomino (MG, MZL, MB), pp. 1–8.
CoGCIG-2018-IshiharaIIHT #behaviour #game studies #implementation
Monte-Carlo Tree Search for Implementation of Dynamic Difficulty Adjustment Fighting Game AIs Having Believable Behaviors (MI, SI, RI, TH, RT), pp. 1–8.
CoGCIG-2018-IshiiIIHT #game studies #implementation
Monte-Carlo Tree Search Implementation of Fighting Game AIs Having Personas (RI, SI, MI, TH, RT), pp. 1–8.
CoGCIG-2018-SironiW #adaptation #analysis #game studies #self #video
Analysis of Self-Adaptive Monte Carlo Tree Search in General Video Game Playing (CFS, MHMW), pp. 1–4.
ICMLICML-2018-BuchholzWM
Quasi-Monte Carlo Variational Inference (AB, FW, SM), pp. 667–676.
ICMLICML-2018-ChatterjiFMBJ #formal method #on the #probability #reduction
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo (NSC, NF, YAM, PLB, MIJ), pp. 763–772.
ICMLICML-2018-FoersterFARXW #infinity #named
DiCE: The Infinitely Differentiable Monte Carlo Estimator (JNF, GF, MAS, TR, EPX, SW), pp. 1524–1533.
ICMLICML-2018-RainforthCYW #on the
On Nesting Monte Carlo Estimators (TR, RC, HY, AW), pp. 4264–4273.
ICMLICML-2018-ZouXG #probability
Stochastic Variance-Reduced Hamilton Monte Carlo Methods (DZ, PX0, QG), pp. 6023–6032.
AIIDEAIIDE-2017-PowleyCW #bound #memory management
Memory Bounded Monte Carlo Tree Search (EJP, PIC, DW), pp. 94–100.
CoGCIG-2017-DemediukTRZLM #algorithm
Monte Carlo tree search based algorithms for dynamic difficulty adjustment (SD, MT, WLR, FZ, XL0, F'M), pp. 53–59.
CoGCIG-2017-IlhanE #game studies #learning #video
Monte Carlo tree search with temporal-difference learning for general video game playing (EI, ASEU), pp. 317–324.
CoGCIG-2017-SantosSM
Monte Carlo tree search experiments in hearthstone (AS, PAS, FSM), pp. 272–279.
CoGCIG-2017-SilvaVT #game studies #using
Using Monte Carlo tree search and google maps to improve game balancing in location-based games (LFMS, WV, FT), pp. 215–222.
ICMLICML-2017-DinhBZM #probability
Probabilistic Path Hamiltonian Monte Carlo (VD, AB, CZ, FAMI), pp. 1009–1018.
ICMLICML-2017-Hoffman #learning #markov #modelling
Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo (MDH), pp. 1510–1519.
ICMLICML-2017-KattOA #learning
Learning in POMDPs with Monte Carlo Tree Search (SK, FAO, CA), pp. 1819–1827.
ICMLICML-2017-Simsekli #difference #equation #markov #probability
Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for Markov Chain Monte Carlo (US), pp. 3200–3209.
ICMLICML-2017-TripuraneniRGT
Magnetic Hamiltonian Monte Carlo (NT, MR, ZG, RET), pp. 3453–3461.
PLDIPLDI-2017-HuangTM #algorithm #compilation #markov #modelling #probability
Compiling Markov chain Monte Carlo algorithms for probabilistic modeling (DH0, JBT, GM), pp. 111–125.
CADECADE-2017-FarberKU #proving
Monte Carlo Tableau Proof Search (MF0, CK, JU), pp. 563–579.
AIIDEAIIDE-2016-DevlinASCR #game studies
Combining Gameplay Data with Monte Carlo Tree Search to Emulate Human Play (SD, AA, NS, PIC, JR), pp. 16–22.
AIIDEAIIDE-2016-KartalSG #data-driven #generative
Data Driven Sokoban Puzzle Generation with Monte Carlo Tree Search (BK, NS, SJG), pp. 58–64.
AIIDEAIIDE-2016-SooLC #using
Generate Believable Causal Plots with User Preferences Using Constrained Monte Carlo Tree Search (VWS, CML, THC), pp. 218–224.
AIIDEAIIDE-2016-UriarteO #modelling #policy #probability
Improving Monte Carlo Tree Search Policies in StarCraft via Probabilistic Models Learned from Replay Data (AU, SO), pp. 100–106.
CoGCIG-2016-GrafP #revisited #simulation
Monte-Carlo simulation balancing revisited (TG, MP), pp. 1–7.
CoGCIG-2016-Ontanon #game studies #realtime
Informed Monte Carlo Tree Search for Real-Time Strategy games (SO), pp. 1–8.
CoGCIG-2016-SoemersSSW #game studies #realtime #video
Enhancements for real-time Monte-Carlo Tree Search in General Video Game Playing (DJNJS, CFS, TS, MHMW), pp. 1–8.
CoGCIG-2016-WaardRB #game studies #video
Monte Carlo Tree Search with options for general video game playing (MdW, DMR, SCJB), pp. 1–8.
ICMLICML-2016-KhandelwalLNS #analysis #on the
On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search (PK, EL, SN, PS), pp. 1319–1328.
ICMLICML-2016-MnihR
Variational Inference for Monte Carlo Objectives (AM, DJR), pp. 2188–2196.
ICMLICML-2016-PaigeW #modelling #network #visual notation
Inference Networks for Sequential Monte Carlo in Graphical Models (BP, FDW), pp. 3040–3049.
ICMLICML-2016-RainforthNLPMDW #markov
Interacting Particle Markov Chain Monte Carlo (TR, CAN, FL, BP, JWvdM, AD, FDW), pp. 2616–2625.
ICMLICML-2016-RoychowdhuryKP #robust #using
Robust Monte Carlo Sampling using Riemannian Nosé-Poincaré Hamiltonian Dynamics (AR, BK, SP0), pp. 2673–2681.
ICMLICML-2016-SimsekliBCR #probability
Stochastic Quasi-Newton Langevin Monte Carlo (US, RB, ATC, GR), pp. 642–651.
CoGCIG-2015-ChangHH #algorithm #analysis #case study #convergence #correctness
Convergence and correctness analysis of Monte-Carlo tree search algorithms: A case study of 2 by 4 Chinese dark chess (HJC, CWH, TsH), pp. 260–266.
CoGCIG-2015-ChuHGHT #algorithm #game studies #knowledge-based #video
Combining pathfmding algorithm with Knowledge-based Monte-Carlo tree search in general video game playing (CYC, HH, ZG, TH, RT), pp. 523–529.
CoGCIG-2015-CowlingWP
Emergent bluffing and inference with Monte Carlo Tree Search (PIC, DW, EJP), pp. 114–121.
CoGCIG-2015-FujikiIV #algorithm #comparison #framework #game studies #platform
A platform for turn-based strategy games, with a comparison of Monte-Carlo algorithms (TF, KI, SV), pp. 407–414.
CoGCIG-2015-ImagawaK #algorithm #game studies
Enhancements in Monte Carlo tree search algorithms for biased game trees (TI, TK), pp. 43–50.
CoGCIG-2015-IvanovoRZL #learning
Combining Monte Carlo tree search and apprenticeship learning for capture the flag (JI, WLR, FZ, XL0), pp. 154–161.
CoGCIG-2015-LiuT
Regulation of exploration for simple regret minimization in Monte-Carlo tree search (YCL, YT), pp. 35–42.
CoGCIG-2015-MizukamiT #modelling #simulation
Building a computer Mahjong player based on Monte Carlo simulation and opponent models (NM, YT), pp. 275–283.
CoGCIG-2015-SatoIW #estimation #multi #using
Estimation of player's preference for cooperative RPGs using multi-strategy Monte-Carlo method (NS, KI, TW), pp. 51–59.
CoGCIG-2015-WangZLHW #game studies
Belief-state Monte-Carlo tree search for Phantom games (JW, TZ, HL, CHH, ICW), pp. 267–274.
CoGCIG-2015-ZhuangLPZ #network #novel #representation
Improving Monte-Carlo tree search for dots-and-boxes with a novel board representation and artificial neural networks (YZ, SL, TVP, CZ), pp. 314–321.
FDGFDG-2015-FischerFVTR
Monte-Carlo Tree Search for Simulated Car Racing (JF, NF, MV, JT, SR).
FDGFDG-2015-ZookHR #analysis #game studies
Monte-Carlo Tree Search for Simulation-based Play Strategy Analysis (AZ, BH, MR).
ICMLICML-2015-Betancourt #scalability
The Fundamental Incompatibility of Scalable Hamiltonian Monte Carlo and Naive Data Subsampling (MB), pp. 533–540.
ICMLICML-2015-ChaoSMS #exponential #integration
Exponential Integration for Hamiltonian Monte Carlo (WLC, JS, DM, FS), pp. 1142–1151.
ICMLICML-2015-NaessethLS
Nested Sequential Monte Carlo Methods (CAN, FL, TBS), pp. 1292–1301.
ICMLICML-2015-SalimansKW #markov
Markov Chain Monte Carlo and Variational Inference: Bridging the Gap (TS, DPK, MW), pp. 1218–1226.
ICMLICML-2015-WangFS #for free #privacy #probability
Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo (YXW, SEF, AJS), pp. 2493–2502.
SACSAC-2015-Rubio-MonteroPG #adaptation #evaluation #framework
Evaluation of an adaptive framework for resilient Monte Carlo executions (AJRM, MARP, RMG), pp. 448–455.
DATEDATE-2015-AfacanBPDB #hybrid
A hybrid Quasi Monte Carlo method for yield aware analog circuit sizing tool (EA, GB, AEP, GD, IFB), pp. 1225–1228.
HPDCHPDC-2015-XiaoCHZ #cpu #gpu
Monte Carlo Based Ray Tracing in CPU-GPU Heterogeneous Systems and Applications in Radiation Therapy (KX, DZC, XSH, BZ), pp. 247–258.
CoGCIG-2014-GrafP #graph
Common fate graph patterns in Monte Carlo Tree Search for computer go (TG, MP), pp. 1–8.
CoGCIG-2014-KimYK #geometry #graph #representation #using
Solving Geometry Friends using Monte-Carlo Tree Search with directed graph representation (HTK, DMY, KJK), pp. 1–2.
CoGCIG-2014-LanctotWPS #heuristic #using
Monte Carlo Tree Search with heuristic evaluations using implicit minimax backups (ML, MHMW, TP, NRS), pp. 1–8.
CoGCIG-2014-SanseloneSSPD #game studies #using
Constrained control of non-playing characters using Monte Carlo Tree Search (MS, SS, CS, DP, YD), pp. 1–8.
CoGCIG-2014-SarrattPJ #convergence
Converging to a player model in Monte-Carlo Tree Search (TS, DVP, AJ), pp. 1–7.
CoGCIG-2014-SephtonCPS #game studies #heuristic
Heuristic move pruning in Monte Carlo Tree Search for the strategic card game Lords of War (NS, PIC, EJP, NHS), pp. 1–7.
CoGCIG-2014-TakLW #game studies
Monte Carlo Tree Search variants for simultaneous move games (MJWT, ML, MHMW), pp. 1–8.
ICMLICML-c1-2014-BardenetDH #adaptation #approach #markov #scalability #towards
Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach (RB, AD, CCH), pp. 405–413.
ICMLICML-c1-2014-LanZS
Spherical Hamiltonian Monte Carlo for Constrained Target Distributions (SL, BZ, BS), pp. 629–637.
ICMLICML-c1-2014-Sohl-DicksteinMD
Hamiltonian Monte Carlo Without Detailed Balance (JSD, MM, MRD), pp. 719–726.
ICMLICML-c1-2014-YangSAM #invariant #kernel
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels (JY, VS, HA, MWM), pp. 485–493.
ICMLICML-c2-2014-ChenFG #probability
Stochastic Gradient Hamiltonian Monte Carlo (TC, EBF, CG), pp. 1683–1691.
ICMLICML-c2-2014-JunB #memory management #performance
Memory (and Time) Efficient Sequential Monte Carlo (SHJ, ABC), pp. 514–522.
ICMLICML-c2-2014-NeufeldGSS #adaptation
Adaptive Monte Carlo via Bandit Allocation (JN, AG, CS, DS), pp. 1944–1952.
ICMLICML-c2-2014-SuttonMPH #equivalence
A new Q(λ) with interim forward view and Monte Carlo equivalence (RSS, ARM, DP, HvH), pp. 568–576.
AIIDEAIIDE-2013-WhitehouseCPR #game studies #knowledge-based #mobile
Integrating Monte Carlo Tree Search with Knowledge-Based Methods to Create Engaging Play in a Commercial Mobile Game (DW, PIC, EJP, JR).
CoGCIG-2013-AlhejaliL #heuristic #programming #search-based #using
Using genetic programming to evolve heuristics for a Monte Carlo Tree Search Ms Pac-Man agent (AMA, SML), pp. 1–8.
CoGCIG-2013-BaierW
Monte-Carlo Tree Search and minimax hybrids (HB, MHMW), pp. 1–8.
CoGCIG-2013-FurtakB #game studies #recursion
Recursive Monte Carlo search for imperfect information games (TF, MB), pp. 1–8.
CoGCIG-2013-IkedaV
Production of various strategies and position control for Monte-Carlo Go - Entertaining human players (KI, SV), pp. 1–8.
CoGCIG-2013-PerezSL #learning #multi #online
Online and offline learning in multi-objective Monte Carlo Tree Search (DPL, SS, SML), pp. 1–8.
CoGCIG-2013-PowleyWC #policy #simulation
Bandits all the way down: UCB1 as a simulation policy in Monte Carlo Tree Search (EJP, DW, PIC), pp. 1–8.
CoGCIG-2013-PowleyWC13a #heuristic #multi #physics #problem
Monte Carlo Tree Search with macro-actions and heuristic route planning for the Multiobjective Physical Travelling Salesman Problem (EJP, DW, PIC), pp. 1–8.
ICMLICML-c1-2013-WilliamsonDX #markov #modelling #parallel #parametricity
Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models (SW, AD, EPX), pp. 98–106.
ICMLICML-c2-2013-CarpentierM #integration #towards
Toward Optimal Stratification for Stratified Monte-Carlo Integration (AC, RM), pp. 28–36.
ICMLICML-c3-2013-WangMF #adaptation
Adaptive Hamiltonian and Riemann Manifold Monte Carlo (ZW, SM, NdF), pp. 1462–1470.
CASECASE-2013-Geldmann #image #simulation #using
Fine registration of SEM and AFM images using Monte Carlo simulations (CG), pp. 813–818.
DATEDATE-2013-SchryverTW #multi
A multi-level Monte Carlo FPGA accelerator for option pricing in the Heston model (CdS, PT, NW), pp. 248–253.
CoGCIG-2012-BaierW
Beam Monte-Carlo Tree Search (HB, MHMW), pp. 227–233.
CoGCIG-2012-NaveedKCCG
A Monte-Carlo path planner for dynamic and partially observable environments (MN0, DEK, AC, LC, PG), pp. 211–218.
CoGCIG-2012-PepelsW
Enhancements for Monte-Carlo Tree Search in Ms Pac-Man (TP, MHMW), pp. 265–272.
CoGCIG-2012-PerezRL
Monte Carlo Tree Search: Long-term versus short-term planning (DPL, PR, SML), pp. 219–226.
CoGCIG-2012-PerickSME #comparison #game studies
Comparison of different selection strategies in Monte-Carlo Tree Search for the game of Tron (PP, DLSP, FM, DE), pp. 242–249.
CoGCIG-2012-PowleyWC #heuristic #physics #problem
Monte Carlo Tree Search with macro-actions and heuristic route planning for the Physical Travelling Salesman Problem (EJP, DW, PIC), pp. 234–241.
CIKMCIKM-2012-EmrichKNRSZ #graph #nondeterminism #probability #query
Exploration of monte-carlo based probabilistic query processing in uncertain graphs (TE, HPK, JN, MR, AS, AZ), pp. 2728–2730.
ICMLICML-2012-WangWHL #learning
Monte Carlo Bayesian Reinforcement Learning (YW, KSW, DH, WSL), p. 105.
ICPRICPR-2012-WangL12a
Hamiltonian Monte Carlo estimator for abrupt motion tracking (FW, ML), pp. 3066–3069.
SIGIRSIGIR-2012-Cummins #modelling #performance #predict #simulation #using
Investigating performance predictors using monte carlo simulation and score distribution models (RC), pp. 1097–1098.
DACDAC-2012-KuoHCKC #design #performance
Efficient trimmed-sample Monte Carlo methodology and yield-aware design flow for analog circuits (CCK, WYH, YHC, JFK, YKC), pp. 1113–1118.
CoGCIG-2011-IkehataI
Monte-Carlo tree search in Ms. Pac-Man (NI, TI), pp. 39–46.
CoGCIG-2011-NijssenW #game studies
Monte-Carlo Tree Search for the game of Scotland Yard (J(AMN, MHMW), pp. 158–165.
CoGCIG-2011-RoblesRL #game studies #learning
Learning non-random moves for playing Othello: Improving Monte Carlo Tree Search (DR, PR, SML), pp. 305–312.
CoGCIG-2011-TongMS #approach
A Monte-Carlo approach for the endgame of Ms. Pac-Man (BKBT, CMM, CWS), pp. 9–15.
CoGCIG-2011-WhitehousePC #game studies #set
Determinization and information set Monte Carlo Tree Search for the card game Dou Di Zhu (DW, EJP, PIC), pp. 87–94.
CoGCIG-2011-WinandsB
αβ-based play-outs in Monte-Carlo Tree Search (MHMW, YB), pp. 110–117.
DACDAC-2011-GongYH #analysis #orthogonal #performance #probability
Fast non-monte-carlo transient noise analysis for high-precision analog/RF circuits by stochastic orthogonal polynomials (FG, HY, LH), pp. 298–303.
DACDAC-2011-IqbalSH #dependence #fault #named #power management #probability #scheduling
SEAL: soft error aware low power scheduling by Monte Carlo state space under the influence of stochastic spatial and temporal dependencies (NI, MAS, JH), pp. 134–139.
DATEDATE-2011-MerrettAWZRMRLFA #analysis #modelling #performance #statistics #variability
Modelling circuit performance variations due to statistical variability: Monte Carlo static timing analysis (MM, PA, YW, MZ, DR, CM, SR, ZL, SBF, AA), pp. 1537–1540.
PDPPDP-2011-PascualRMBCL #case study #performance
More Efficient Executions of Monte Carlo Fusion Codes by Means of Montera: The ISDEP Use Case (MARP, AJRM, RM, AB, FC, IML), pp. 380–384.
FASEFASE-2011-OudinetDGLP #model checking
Uniform Monte-Carlo Model Checking (JO, AD, MCG, RL, SP), pp. 127–140.
AIIDEAIIDE-2010-LaviersS #approach #game studies #generative
A Monte Carlo Approach for Football Play Generation (KRL, GS).
CoGCIG-2010-TeytaudT #algorithm #on the
On the huge benefit of decisive moves in Monte-Carlo Tree Search algorithms (FT, OT), pp. 359–364.
ICPRICPR-2010-KimL #markov #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 #markov #using
A Graph Matching Algorithm Using Data-Driven Markov Chain Monte Carlo Sampling (JL, MC, KML), pp. 2816–2819.
ICPRICPR-2010-ZhouL #approximate #optimisation #performance
Efficient Polygonal Approximation of Digital Curves via Monte Carlo Optimization (XZ, YL), pp. 3513–3516.
DACDAC-2010-VeetilCSB #performance #resource management
Efficient smart monte carlo based SSTA on graphics processing units with improved resource utilization (VV, YHC, DS, DB), pp. 793–798.
DATEDATE-2010-IqbalSH10a #estimation #execution #graph #named
DAGS: Distribution agnostic sequential Monte Carlo scheme for task execution time estimation (NI, MAS, JH), pp. 1645–1648.
DATEDATE-2010-JaffariA #estimation
Practical Monte-Carlo based timing yield estimation of digital circuits (JJ, MA), pp. 807–812.
DATEDATE-2010-KanoriaMM #analysis #markov #statistics #using
Statistical static timing analysis using Markov chain Monte Carlo (YK, SM, AM), pp. 813–818.
CoGCIG-2009-WardC
Monte Carlo search applied to card selection in Magic: The Gathering (CDW, PIC), pp. 9–16.
ICMLICML-2009-SilverT #simulation
Monte-Carlo simulation balancing (DS, GT), pp. 945–952.
CAVCAV-2009-KitchenK #constraints #integer #markov
A Markov Chain Monte Carlo Sampler for Mixed Boolean/Integer Constraints (NK, AK), pp. 446–461.
SIGMODSIGMOD-2008-JampaniXWPJH #approach #named #nondeterminism
MCDB: a monte carlo approach to managing uncertain data (RJ, FX, MW, LLP, CMJ, PJH), pp. 687–700.
AIIDEAIIDE-2008-ChaslotBSS #framework #game studies
Monte-Carlo Tree Search: A New Framework for Game AI (GC, SB, IS, PS).
CoGCIG-2008-ChildsBK
Transpositions and move groups in Monte Carlo tree search (BEC, JHB, LK), pp. 389–395.
CoGCIG-2008-ShibaharaK #simulation
Combining final score with winning percentage by sigmoid function in Monte-Carlo simulations (KS, YK), pp. 183–190.
CoGCIG-2008-TakeuchiKY #evaluation
Evaluation of Monte Carlo tree search and the application to Go (ST, TK, KY), pp. 191–198.
ICMLICML-2008-SalakhutdinovM08a #markov #matrix #probability #using
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo (RS, AM), pp. 880–887.
ICPRICPR-2008-Sakai #approach #classification #incremental
Monte Carlo subspace method: An incremental approach to high-dimensional data classification (TS), pp. 1–4.
PADLPADL-2008-KellerCCSB #generative
Specialising Simulator Generators for High-Performance Monte-Carlo Methods (GK, HCM, MMTC, DS, CBK), pp. 116–132.
DACDAC-2008-VeetilSB #analysis #incremental #performance #statistics
Efficient Monte Carlo based incremental statistical timing analysis (VV, DS, DB), pp. 676–681.
CoGCIG-2007-WangG #simulation
Modifications of UCT and sequence-like simulations for Monte-Carlo Go (YW, SG), pp. 175–182.
CHICHI-2007-StrachanWM #navigation
Show me the way to Monte Carlo: density-based trajectory navigation (SS, JW, RMS), pp. 1245–1248.
ESEC-FSEESEC-FSE-2007-SankaranarayananCJI #constraints #feedback #generative #using
State space exploration using feedback constraint generation and Monte-Carlo sampling (SS, RMC, GJ, FI), pp. 321–330.
DACDAC-2007-KimJH #estimation #performance
Fast, Non-Monte-Carlo Estimation of Transient Performance Variation Due to Device Mismatch (JK, KDJ, MAH), pp. 440–443.
DATEDATE-2007-SingheeR #novel #performance #simulation #statistics
Statistical blockade: a novel method for very fast Monte Carlo simulation of rare circuit events, and its application (AS, RAR), pp. 1379–1384.
PDPPDP-2007-DaneseLBGNS #simulation
An Application Specific Processor for Montecarlo Simulations (GD, FL, MB, MG, NN, AS), pp. 262–269.
CoGCIG-2006-BouzyC #learning
Monte-Carlo Go Reinforcement Learning Experiments (BB, GC), pp. 187–194.
ICPRICPR-v1-2006-WenGL #clustering #detection #markov
Markov Chain Monte Carlo Data Association for Merge and Split Detection in Tracking Protein Clusters (QW, JG, KLP), pp. 1030–1033.
ICPRICPR-v1-2006-XueZZ #framework #multi
An integrated Monte Carlo data association framework for multi-object tracking (JX, NZ, XZ), pp. 703–706.
ICPRICPR-v2-2006-KimK06b #estimation #graph #modelling #multi #online
Multi-modal Sequential Monte Carlo for On-Line Hierarchical Graph Structure Estimation in Model-based Scene Interpretation (SK, ISK), pp. 251–254.
ICPRICPR-v2-2006-YuCMW #detection #markov #multi
Boosted Markov Chain Monte Carlo Data Association for Multiple Target Detection and Tracking (QY, IC, GGM, BW), pp. 675–678.
MBTMBT-2006-CallananGRSTZ #approach #runtime #verification
Runtime Verification for High-Confidence Systems: A Monte Carlo Approach (SC, RG, AR, SAS, MRT, EZ), pp. 41–52.
CoGCIG-2005-CazenaveH #game studies
Combining Tactical Search and Monte-Carlo in the Game of Go (TC, BH).
CoGCIG-2005-ChungBS #game studies
Monte Carlo Planning in RTS Games (MC, MB, JS).
ICMLICML-2005-EspositoS #classification #comparison
Experimental comparison between bagging and Monte Carlo ensemble classification (RE, LS), pp. 209–216.
TACASTACAS-2005-GrosuS #model checking
Monte Carlo Model Checking (RG, SAS), pp. 271–286.
ICMLICML-2004-EspositoS #analysis #classification
A Monte Carlo analysis of ensemble classification (RE, LS).
ICPRICPR-v3-2004-MatsuiCUM #markov #recognition #using
Bayesian Face Recognition using a Markov Chain Monte Carlo Method (AM, SC, FU, TM), pp. 918–921.
ICPRICPR-v4-2004-LinWH
Articulate Hand Motion Capturing Based on a Monte Carlo Nelder-Mead Simplex Tracker (JL, YW, TSH), pp. 975–978.
ICPRICPR-v4-2004-MurakitaII #markov #using
Human Tracking using Floor Sensors based on the Markov Chain Monte Carlo Method (TM, TI, HI), pp. 917–920.
SIGMODSIGMOD-2002-ProcopiucJAM #algorithm #clustering #performance
A Monte Carlo algorithm for fast projective clustering (CMP, MJ, PKA, TMM), pp. 418–427.
ICMLICML-2002-FitzgibbonDA #approximate #polynomial
Univariate Polynomial Inference by Monte Carlo Message Length Approximation (LJF, DLD, LA), pp. 147–154.
ICMLICML-2002-StrensBE #markov #optimisation #using
Markov Chain Monte Carlo Sampling using Direct Search Optimization (MJAS, MB, NE), pp. 602–609.
ICMLICML-2002-ThamDR #classification #learning #markov #using
Sparse Bayesian Learning for Regression and Classification using Markov Chain Monte Carlo (SST, AD, KR), pp. 634–641.
ICPRICPR-v1-2002-KatoKS #distributed #named #smarttech
VizWear-Active: Distributed Monte Carlo Face Tracking for Wearable Active Cameras (TK, TK, KS), pp. 395–400.
ICPRICPR-v3-2002-BaesensECV #classification #learning #markov #network #using
Learning Bayesian Network Classifiers for Credit Scoring Using Markov Chain Monte Carlo Search (BB, MEP, RC, JV), pp. 49–52.
ICPRICPR-v4-2002-Ichimura #estimation #image #probability #sequence #using
Stochastic Filtering for Motion Trajectory in Image Sequences Using a Monte Carlo Filter with Estimation of Hyper-Parameters (NI), pp. 68–73.
POPLPOPL-2001-Monniaux #analysis #probability #source code
An abstract Monte-Carlo method for the analysis of probabilistic programs (DM), pp. 93–101.
SACSAC-2001-DowellB #graph #mobile #network #random #simulation #validation
Connectivity of random graphs and mobile networks: validation of Monte Carlo simulation results (LJD, MLB), pp. 77–81.
ICPRICPR-v1-2000-GidasRA
Tracking of Moving Objects in Cluttered Environments via Monte Carlo Filter (BG, CR, MPdA), pp. 1175–1178.
ICPRICPR-v1-2000-MossH #markov #using
Alignment and Correspondence Using Markov Chain Monte Carlo (SM, ERH), pp. 1928–1931.
ICMLICML-1999-ThrunLF #learning #markov #modelling #parametricity #probability #process
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes (ST, JL, DF), pp. 415–424.
PDPPDP-1999-OdorKVR #architecture #effectiveness #parallel #simulation #string
Effective Monte Carlo simulation on System-V massively parallel associative string processing architecture (, AK, GV, FR), pp. 281–288.
DATEEDTC-1997-SaxenaNH #approach #estimation
Monte-Carlo approach for power estimation in sequential circuits (VS, FNN, INH), pp. 416–420.
KDDKDD-1996-Smyth #clustering #using
Clustering Using Monte Carlo Cross-Validation (PS), pp. 126–133.
KDDKDD-1996-StolorzC #learning #markov #visual notation
Harnessing Graphical Structure in Markov Chain Monte Carlo Learning (PES, PCC), pp. 134–139.
SEKESEKE-1996-JamoussiB #generative #performance #random testing #testing
Efficient Monte Carlo Method for Generating Random Test Data from Irregular Test Regions (AJ, FBB), pp. 17–24.
SACSAC-1993-HashemiCST #network #paradigm #predict
Prediction Capability of Neural Networks Trained by Monte-Carlo Paradigm (RRH, AHC, NLS, JRT), pp. 9–13.
STOCSTOC-1991-BabaiCFLS #algorithm #performance #permutation
Fast Monte Carlo Algorithms for Permutation Groups (LB, GC, LF, EML, ÁS), pp. 90–100.
DACDAC-1970-MitchellG #analysis #design #simulation
A simulation program for monte carlo analysis and design (EELM, DG), pp. 265–270.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.