Compressed Predictive States Efficient Learning and Planning with Compressed Predictive States arXiv:1312.0286v2 [cs.LG] 20 Jul 2014

Source URL: arxiv.org

• Markov processes
• Machine learning
• Markov models
• Predictive state representation
• Matrix
• Markov chain
• Markov decision process
• G factor

REV_ISS_WEB_COGS_12101_38

Source URL: cocosci.berkeley.edu

• Statistics
• Statistical theory
• Statistical inference
• Philosophy of science
• Bayesian statistics
• Bayesian network
• Bayesian inference
• Bayesian probability
• Decision theory
• Prior probability
• Concept learning
• Markov chain Monte Carlo

Appears as Chapter 5 of the Handbook of Markov Chain Monte Carlo Edited by Steve Brooks, Andrew Gelman, Galin Jones, and Xiao-Li Meng arXiv:1206.1901v1 [stat.CO] 9 JunChapman & Hall / CRC Press, 2011

Source URL: arxiv.org

• Physics
• Hamiltonian mechanics
• Chemistry
• Theoretical physics
• Dynamical systems
• Classical mechanics
• Quantum mechanics
• Quantum chemistry
• Hamiltonian
• Limit of a function
• Hamiltonian system
• Analytical mechanics

Exploring the structure of mental representations by implementing computer algorithms with people Adam N. Sanborn University of Warwick Thomas L. Griffiths

Source URL: cocosci.berkeley.edu

• Statistics
• Monte Carlo methods
• Statistical theory
• Probability
• Markov chain Monte Carlo
• Markov models
• Computational statistics
• Probability distribution
• MetropolisHastings algorithm
• Markov chain
• Normal distribution
• Hybrid Monte Carlo

Cognitive Science–1431 Copyright © 2014 Cognitive Science Society, Inc. All rights reserved. ISSN: printonline DOI: cogsAnalyzing the Rate at Which Languages Lose

Source URL: cocosci.berkeley.edu

• Statistics
• Cognition
• Language acquisition
• Learning
• Statistical inference
• Cognitive science
• Machine learning
• Bayesian network
• Bayesian inference
• Markov chain
• Universal grammar
• Inductive bias

Journal of International Economics

Source URL: www.ssc.wisc.edu

• Probability theory
• Stochastic processes
• Statistics
• Data
• Markov models
• Graph theory
• Markov chain
• Random walk
• Forecasting
• Estimation theory

Bayesian Learning via Stochastic Gradient Langevin Dynamics Max Welling D. Bren School of Information and Computer Science, University of California, Irvine, CA, USA Yee Whye Teh

Source URL: www.icml-2011.org

• Applied mathematics
• Statistical randomness
• Probability and statistics
• Monte Carlo methods
• Markov models
• Statistical mechanics
• Stochastic optimization
• Computational statistics
• Markov chain Monte Carlo
• Stochastic approximation
• Langevin dynamics
• Bayesian network

A Level-set Hit-and-run Sampler for Quasi-Concave Distributions Shane T. Jensen and Dean P. Foster Department of Statistics, The Wharton School, University of Pennsylvania Abstract

Source URL: www-stat.wharton.upenn.edu

• Monte Carlo methods
• Markov chain Monte Carlo
• Non-uniform random numbers
• Probability distributions
• Computational statistics
• Gibbs sampling
• Rejection sampling
• MetropolisHastings algorithm
• Slice sampling
• Bayesian network
• Quasiconvex function
• Normal distribution

Two Characterizations of Success of Ergodic Markov Chain Families for Combinatorial Optimization Swagato Sanyal1 and Somenath Biswas2 1 School of Technology and Computer Science

Source URL: www.cse.iitk.ac.in

A comparison of variational and Markov Chain Monte Carlo methods for inference in partially observed stochastic dynamic systems. Yuan Shen Neural Computing Research Group Aston University

Source URL: www0.cs.ucl.ac.uk