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Hidden Markov models
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#	Item
561	Representing hierarchical POMDPs as DBNs for multi-scale robot localization Georgios Theocharous THEOCHAR @ AI . MIT. EDU Kevin Murphy MURPHYK @ AI . MIT. EDU Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2004-07-01 07:47:50 Dynamic programming Stochastic control Hierarchical hidden Markov model Partially observable Markov decision process Hidden Markov model Markov decision process Expectation–maximization algorithm Markov chain Belief propagation Statistics Markov processes Markov models
562	Factored Conditional Restricted Boltzmann Machines for Modeling Motion Style Graham W. Taylor GWTAYLOR @ CS . TORONTO . EDU Geoffrey E. Hinton Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2009-05-18 12:17:00 Probability and statistics Neural networks Machine learning Boltzmann machine Generative model Graphical model Hidden Markov model Bayesian network Ludwig Boltzmann Statistical models Statistics Bayesian statistics
563	1 Dynamic Processing Allocation in Video Daozheng Chen, Student Member, IEEE, Mustafa Bilgic, Lise Getoor, Member, IEEE, and David Jacobs, Member, IEEE, Abstract—Large stores of digital video pose severe computational Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2011-01-25 16:50:47 Mathematics Operations research Markov processes Machine learning Algorithm Mathematical logic Dynamic programming Hidden Markov model Markov chain Statistics Markov models Probability and statistics
564	Discovering Latent Structure in Task-Oriented Dialogues Ke Zhai∗ Jason D. Williams Computer Science, University of Maryland Microsoft Research College Park, MD 20740 Add to Reading List Source URL: www.umiacs.umd.edu Language: English - Date: 2014-04-23 13:20:38 Machine learning Statistical natural language processing Computational linguistics Bioinformatics Hidden Markov model Vehicle Identification Number Speech recognition Language model Mixture model Statistics Markov models Probability and statistics
565	Painless Unsupervised Learning with Features Taylor Berg-Kirkpatrick Alexandre Bouchard-Cˆot´e John DeNero Computer Science Division University of California at Berkeley Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2010-08-26 16:46:00 Computational linguistics Markov models Corpus linguistics Speech recognition Machine learning Expectation–maximization algorithm Hidden Markov model N-gram Part-of-speech tagging Linguistics Statistics Science
566	Hidden Markov Models • Generative, rather than descriptive model. – Objects produced by random process. • Dependencies in process, some random events influence others. Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2009-04-08 09:40:03 Probability and statistics Dynamic programming Bioinformatics Hidden Markov model Markov chain Forward–backward algorithm Continuous-time Markov process Markov models Statistics Markov processes
567	Microsoft PowerPoint - Image classification by a Two Dimensional Hidden Markov_1.ppt Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2003-12-08 10:54:43 Markov chain HMM Statistical classification Markov random field Viterbi algorithm Markov models Statistics Probability
568	Efficient Resource-constrained Retrospective Analysis of Long Video Sequences Daozheng Chen, Mustafa Bilgic, Lise Getoor, David Jacobs Department of Computer Science University of Maryland, College Park Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2011-12-26 12:18:04 Mathematics Cybernetics Algorithm Mathematical logic Theoretical computer science Hidden Markov model Forward–backward algorithm Mixture model Sampling Statistics Machine learning Markov models
569	Inverting the Viterbi Algorithm: An Abstract Framework for Structure Design Michael Schnall-Levin [removed] Leonid Chindelevitch Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-05-12 14:01:36 Probability and statistics Viterbi algorithm Hidden Markov model Dynamic programming Stochastic context-free grammar Markov chain Fisher–Yates shuffle Baum–Welch algorithm Algorithm Markov models Statistics Mathematics
570	A Graphical Model for Protein Secondary Structure Prediction Wei Chu [removed] Zoubin Ghahramani [removed] Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:20:56 Protein secondary structure Stereochemistry Protein structure prediction Hidden Markov model STING Protein structure Biology Applied mathematics Bioinformatics Science Markov models

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