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Monte Carlo algorithm
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41	A Lock-free Multithreaded Monte-Carlo Tree Search Algorithm Markus Enzenberger and Martin M¨uller Department of Computing Science, University of Alberta Corresponding author: Add to Reading List Source URL: webdocs.cs.ualberta.ca Language: English - Date: 2015-11-16 19:05:00
42	Implementation of a Component-By-Component Algorithm to Generate Small Low-Discrepancy Samples Benjamin Doerr, Michael Gnewuch, and Magnus Wahlstr¨om Abstract In [B. Doerr, M. Gnewuch, P. Kritzer, F. Pillichshammer. Mo Add to Reading List Source URL: www.numerik.uni-kiel.de Language: English - Date: 2009-06-23 07:05:42 Quasirandomness Diophantine approximation Low-discrepancy sequence Numerical analysis Random number generation Randomized rounding Randomized algorithm Quasi-Monte Carlo method
43	Distributed and Adaptive Darting Monte Carlo through Regenerations Sungjin Ahn Department of Computer Science University of California, Irvine Irvine, CA, USA Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2013-04-11 10:50:54 Markov models Markov chain Monte Carlo Computational statistics Markov processes Markov chain Metropolis–Hastings algorithm Rejection sampling Mixture model Random walk Statistics Probability and statistics Monte Carlo methods
44	Bayesian Learning via Stochastic Gradient Langevin Dynamics Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2011-05-21 11:48:52 Computational statistics Stochastic optimization Statistical mechanics Estimation theory Markov chain Monte Carlo Langevin dynamics Stochastic approximation Metropolis–Hastings algorithm Mixture model Statistics Probability and statistics Monte Carlo methods
45	Randomized Algorithms for Counting, Rare-Events Estimation and Optimization Reuven Rubinstein Faculty of Industrial Engineering and Technion, Israel Institute of Technology, Haifa , Israel Add to Reading List Source URL: www.eurandom.tue.nl Language: English - Date: 2009-03-23 10:55:31 Monte Carlo methods Reuven Rubinstein Year of birth missing Markov chain Monte Carlo Mathematical optimization Algorithm Randomized algorithm Combinatorics Combinatorial optimization Applied mathematics Theoretical computer science Mathematics
46	High Performance Computing II Lecture 13 Topic 3: Monte Carlo Simulation of Magnetic Materials (continued) The program ising.c implements a serial version of the Metropolis Monte Carlo algorithm applied to the 2-D Ising Add to Reading List Source URL: www.physics.buffalo.edu Language: English - Date: 2014-03-25 12:14:10 Quantum phases Quantum field theory Ising model Ferromagnetism Paramagnetism Magnet Spin Spin glass Monte Carlo method in statistical physics Physics Statistical mechanics Magnetic ordering
47	High Performance Computing II Lecture 15 Topic 3: Monte Carlo Simulation of Magnetic Materials (continued) Monte Carlo simulations close to a phase transition are affected by critical slowing Add to Reading List Source URL: www.physics.buffalo.edu Language: English - Date: 2014-03-25 12:14:10 Monte Carlo methods Lattice models Mathematics Swendsen–Wang algorithm Ising model Wolff algorithm Percolation theory Cluster labeling K-nearest neighbor algorithm Physics Statistical mechanics Probability and statistics
48	arXiv:1301.4168v2 [cs.LG] 16 MarHerded Gibbs Sampling Luke Bornn Harvard University Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2013-04-19 06:38:10 Applied mathematics Statistical mechanics Markov chain Monte Carlo Gibbs sampling Monte Carlo methods Conditional random field Gibbs algorithm Markov chain Viterbi algorithm Statistics Probability and statistics Markov models
49	Evidence Estimation for Bayesian Partially Observed MRFs Yutian Chen Department of Computer Science University of California, Irvine Irvine, CA 92697 Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2013-02-14 03:02:58 Normal distribution Expectation–maximization algorithm Variational Bayesian methods Bayesian network Markov chain Monte Carlo Maximum likelihood Deviance information criterion Pierre-Simon Laplace Markov random field Statistics Bayesian statistics Marginal likelihood
50	Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring Sungjin Ahn Dept. of Computer Science, UC Irvine, Irvine, CA, USA SUNGJIA @ ICS . UCI . EDU Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2012-05-22 12:55:14 Fisher information Markov chain Monte Carlo Normal distribution Stochastic gradient descent Maximum a posteriori estimation Confidence interval Central limit theorem Score Expectation–maximization algorithm Statistics Estimation theory Maximum likelihood

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