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Probability and statistics / Markov models / Information theory / Estimation theory / Philosophy of thermal and statistical physics / Entropy / Kullback–Leibler divergence / Hidden Markov model / Loss function / Statistics / Statistical theory / Software


Active Learning for Hidden Markov Models: Objective Functions and Algorithms Brigham Anderson Andrew Moore Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA[removed]USA
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Document Date: 2008-12-01 11:14:33

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Neural Information Processing Systems / MIT Press / Lewis D. D. / /

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Germany / Jordan / United States / /

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Carnegie Mellon University / University of Cambridge / /

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word processing / online learning / committee algorithm / machine learning applications / computing / text/speech processing / text processing fields / Active learning algorithms / bayesian networks / learning algorithms / /

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National Science Foundation / University of Cambridge / MIT / Cambridge Univ. / S|T / Carnegie Mellon University / Pittsburgh / Objective Functions and Algorithms Brigham Anderson Andrew Moore Department of Computer Science / /

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Active Learning / Brigham Anderson Andrew Moore / Sajid Siddiqi / Morgan Kaufmann / /

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New Brunswick / Pennsylvania / California / /

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Machine Learning / Lecture Notes in Computer Science / /

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speech recognition / artificial intelligence / Viterbi algorithm / committee algorithm / Active learning algorithms / machine learning / ForwardBackward algorithm / simulation / following algorithms / /

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