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Stochastic process
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#	Item
451	Truncation-free Stochastic Variational Inference for Bayesian Nonparametric Models Chong Wang⇤ Machine Learning Department Carnegie Mellon University [removed] Add to Reading List Source URL: www.cs.columbia.edu Language: English - Date: 2015-03-12 00:16:23 Dirichlet process Latent Dirichlet allocation Mixture model Bayesian inference Importance sampling Inference Conjugate prior Hierarchical Bayes model Dirichlet distribution Statistics Bayesian statistics Variational Bayesian methods
452	Stochastic Processes: I • consider “bowl of worms” model for oscilloscope experiment: SAPAscope[removed] Add to Reading List Source URL: faculty.washington.edu Language: English - Date: 2015-03-24 16:45:21 Covariance Stationary process Autocovariance XT Time series Statistics Covariance and correlation Covariance function
453	Two stochastic dynamic programming problems by model-free actor-critic recurrent-network learning in non-Markovian settings Eiji Mizutani Stuart E. Dreyfus Add to Reading List Source URL: www.ieor.berkeley.edu Language: English - Date: 2008-07-16 21:59:54 Dynamic programming Stochastic control Markov models Operations research Markov decision process Reinforcement learning Recurrent neural network Statistics Control theory Markov processes
454	Markov Decision Processes and the Modelling of Patient Flows Anthony Clissold Supervised by Professor Jerzy Filar Flinders University 1 Add to Reading List Source URL: vrs.amsi.org.au Language: English - Date: 2014-09-04 22:39:09 Markov chain Markov decision process Stochastic matrix Matrix Reinforcement learning Models of DNA evolution Statistics Markov models Markov processes
455	Simplicial Label Correcting Algorithms for Continuous Stochastic Shortest Path Problems Dmitry S. Yershov Steven M. LaValle Add to Reading List Source URL: msl.cs.uiuc.edu Language: English - Date: 2013-09-10 21:22:09 Stochastic control Optimal control Dynamic programming Markov models Mathematical optimization Hamilton–Jacobi–Bellman equation Markov decision process Discretization Stochastic differential equation Statistics Mathematics Control theory
456	An Experimental Comparison of Classical, FOND and Probabilistic Planning Andreas Hertle, Christian Dornhege, Thomas Keller, Robert Mattm¨ uller, Manuela Ortlieb, and Bernhard Nebel University of Freiburg, 79110 Freiburg Add to Reading List Source URL: gki.informatik.uni-freiburg.de Language: English - Date: 2014-07-07 07:15:35 Markov processes Stochastic control Planning Motion planning Markov decision process Reinforcement learning Statistics Automated planning and scheduling Dynamic programming
457	Generalized Value Functions for Large Action Sets Jason Pazis Ronald Parr Department of Computer Science, Duke University, Durham, NC[removed]USA Abstract Add to Reading List Source URL: www.cs.duke.edu Language: English - Date: 2011-05-11 14:49:02 Dynamic programming Abstract algebra Linear algebra Stochastic control Markov processes Markov decision process Reinforcement learning Function Q-learning Mathematics Algebra Statistics
458	Coordinated Reinforcement Learning Carlos Guestrin Computer Science Department, Stanford University, Stanford, CA[removed]Michail Lagoudakis Ronald Parr Department of Computer Science, Duke University, Durham, NC 27708 Add to Reading List Source URL: www.cs.duke.edu Language: English - Date: 2012-05-29 14:42:02 Dynamic programming Markov processes Stochastic control Operations research Functions and mappings Reinforcement learning Q-learning Markov decision process Automated planning and scheduling Statistics Control theory Mathematics
459	Better Be Lucky Than Good: Exceeding Expectations in MDP Evaluation Thomas Keller and Florian Geißer University of Freiburg Freiburg, Germany {tkeller,geisserf}@informatik.uni-freiburg.de Add to Reading List Source URL: gki.informatik.uni-freiburg.de Language: English - Date: 2015-03-07 08:48:57 Dynamic programming Stochastic control Markov decision process Reinforcement learning Markov chain Valuation Secretary problem Statistics Markov processes Markov models
460	Past, Present, and Future: An Optimal Online Algorithm for Single-Player GDL-II Games 1 ¨ Florian Geißer and Thomas Keller and Robert Mattmuller Add to Reading List Source URL: gki.informatik.uni-freiburg.de Language: English - Date: 2014-08-08 08:44:39 Stochastic control Control theory Search algorithms Partially observable Markov decision process Markov decision process Tree traversal Game theory Statistics Dynamic programming Markov processes

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