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Metropolis–Hastings algorithm
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61	%A L. Ingber %T Adaptive simulated annealing (ASA): Lessons learned %J Control and Cybernetics %D 1995 %P (to be published) This is an invited paper to a special issue of the Polish Journal Control and Cybernetics on “ Add to Reading List Source URL: www.ingber.com Language: English - Date: 2002-01-14 20:39:05 Numerical analysis Mathematical analysis Mathematics Simulated annealing Markov chain Monte Carlo Maxwell–Boltzmann distribution Metropolis–Hastings algorithm Partition function Quantum annealing Monte Carlo methods Adaptive simulated annealing Mathematical optimization
62	ASA OPTIONS Lester Ingber Abstract Adaptive Simulated Annealing (ASA) is a C-language code that finds the best global fit of a nonlinear cost-function over a D-dimensional space. ASA has over 100 OPTIONS to provide robus Add to Reading List Source URL: www.ingber.com Language: English - Date: 2011-06-15 18:00:58 Adaptive simulated annealing Mathematical optimization Mathematics Simulated annealing Stochastic optimization Maxwell–Boltzmann distribution Metropolis–Hastings algorithm Partition function Annealing Monte Carlo methods Numerical analysis Mathematical analysis
63	A Bayesian Matrix Factorization Model for Relational Data Ajit P. Singh Department of Electrical Engineering University of Washington Seattle, WA 98195, USA Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2010-06-12 22:03:53 Statistical theory Monte Carlo methods Regression analysis Conjugate prior Metropolis–Hastings algorithm Generalized linear model Maximum likelihood Variational Bayesian methods Bayesian inference Statistics Bayesian statistics Estimation theory
64	A Bayesian Matrix Model for Relational Data Geoffrey J. Gordon Machine Learning Department Carnegie Mellon University Pittsburgh, PA 15213, USA Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2009-12-01 11:19:09 Statistical theory Markov chain Monte Carlo Multivariate statistics Conjugate prior Metropolis–Hastings algorithm Maximum likelihood Bayesian inference Generalized linear model Gibbs sampling Statistics Bayesian statistics Estimation theory
65	OH et al.: MARKOV CHAIN MONTE CARLO DATA ASSOCIATION FOR MULTIPLE-TARGET TRACKING 1 Markov Chain Monte Carlo Data Association for Multiple-Target Tracking Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2005-07-14 20:46:46 Computational statistics Robot control Markov processes Markov chain Particle filter Kalman filter Stochastic process Metropolis–Hastings algorithm Estimation theory Statistics Markov models Monte Carlo methods
66	The Bayesian Approach to Inverse Problems Andrew M. Stuart, Mathematics Institute Add to Reading List Source URL: www.stats.ox.ac.uk Language: English - Date: 2011-04-07 16:02:52 Differential equations Markov models Monte Carlo methods Radon–Nikodym theorem Stochastic differential equation Markov chain Random walk Metropolis–Hastings algorithm Gaussian measure Statistics Mathematical analysis Stochastic processes
67	Phase transition Spontaneous ordering (symmetry breaking) at critical temperature Add to Reading List Source URL: physics.bu.edu Language: English - Date: 2013-10-24 15:15:12 Statistical mechanics Monte Carlo methods Markov chain Monte Carlo Ising model Markov chain Metropolis–Hastings algorithm Sampling Importance sampling Probability Physics Statistics Probability and statistics
68	Lecture notes on Markov Chain Monte Carlo methods Furio Ercolessi Dipartimento di Fisica, Universit` Add to Reading List Source URL: www.fisica.uniud.it Language: English - Date: 2009-03-30 07:06:17 Probability and statistics Monte Carlo methods Markov chain Monte Carlo Markov chain Metropolis–Hastings algorithm Stochastic matrix Chapman–Kolmogorov equation Detailed balance Expected value Statistics Markov models Markov processes
69	Wang-Landau sampling for Quantum Monte Carlo Stefan Wessel Add to Reading List Source URL: www.comp-phys.org Language: English - Date: 2007-06-01 03:38:15 Condensed matter physics Density of states Quantum mechanics Metropolis–Hastings algorithm Wang and Landau algorithm Topological order Physics Statistical mechanics Markov chain Monte Carlo
70	Training Restricted Boltzmann Machines: An Introduction⋆ Asja Fischer1,2 and Christian Igel2 1 Add to Reading List Source URL: image.diku.dk Language: English - Date: 2013-11-19 07:56:20 Graphical models Statistical theory Markov processes Networks Markov random field Markov chain Boltzmann machine Bayesian network Metropolis–Hastings algorithm Statistics Probability and statistics Markov models

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