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Conditional random field
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91	Webpage Understanding: an Integrated Approach Jun Zhu ∗ Dept. of Comp. Sci. & Tech. Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2007-06-15 03:38:48 Mathematics Statistics Machine learning Artificial intelligence Probability theory Conditional random field Hidden Markov model Pattern recognition Markov random field Theoretical computer science Graphical models Applied mathematics
92	Effect of Non-linear Deep Architecture in Sequence Labeling Mengqiu Wang MENGQIU @ CS . STANFORD . EDU Christopher D. Manning MANNING @ CS . STANFORD . EDU Add to Reading List Source URL: cs.stanford.edu Language: English - Date: 2013-05-15 05:53:10 Mathematics Science Computational neuroscience Conditional random field Theoretical computer science Perceptron Chunking Artificial neuron Supervised learning Neural networks Machine learning Statistics
93	Hidden Conditional Random Fields for Phone Recognition Yun-Hsuan Sung 1 and Dan Jurafsky 2 1 Electrical Engineering, Stanford University Add to Reading List Source URL: nlp.stanford.edu Language: English - Date: 2010-01-07 17:30:55 Probability and statistics Probability Hidden Markov model Conditional random field Speech recognition Mutual information Sequence labeling Generative model Viterbi algorithm Statistics Machine learning Markov models
94	FROM FLAT DIRECT MODELS TO SEGMENTAL CRF MODELS Geoffrey Zweig and Patrick Nguyen Microsoft Corporation One Microsoft Way, Redmond, WAABSTRACT This paper summarizes recent work at Microsoft on the development of n Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2010-01-06 19:40:40 Computational linguistics Conditional random field Maximum-entropy Markov model Speech recognition N-gram Language model Dynamic programming Part-of-speech tagging Information extraction Markov models Science Probability
95	MAXIMUM CONDITIONAL LIKELIHOOD LINEAR REGRESSION AND MAXIMUM A POSTERIORI FOR HIDDEN CONDITIONAL RANDOM FIELDS SPEAKER ADAPTATION Yun-Hsuan Sung,1 Constantinos Boulis,2 Dan Jurafsky3 Electrical Engineering,1 Linguistics2 Add to Reading List Source URL: nlp.stanford.edu Language: English - Date: 2008-04-28 14:26:34 Econometrics Machine learning Markov models Hidden Markov model Maximum likelihood Linear regression Pattern recognition Normal distribution Conditional random field Statistics Estimation theory Regression analysis
96	SCARF: A Segmental Conditional Random Field Toolkit for Speech Recognition Geoffrey Zweig and Patrick Nguyen Microsoft Corporation One Microsoft Way, Redmond, WAgzweig, Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2010-05-11 19:52:41 Speech recognition Probability Markov models Statistical natural language processing Phonetics Conditional random field N-gram Language model Acoustic model Computational linguistics Linguistics Science
97	Proceedings of the 16th International IEEE Annual Conference on Intelligent Transportation Systems (ITSC 2013), The Hague, The Netherlands, October 6-9, 2013 MoB3.2 Add to Reading List Source URL: www.mrt.kit.edu Language: English - Date: 2014-06-13 04:07:58 Statistical models Probability and statistics Mathematics Perception Belief propagation Coding theory Bayesian network Conditional random field Visual perception Graphical models Statistics Bayesian statistics
98	A Segmental CRF Approach to Large Vocabulary Continuous Speech Recognition Geoffrey Zweig and Patrick Nguyen Microsoft Research, Redmond, WA {gzweig,panguyen}@microsoft.com Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2009-09-05 12:53:28 Computational linguistics Statistical natural language processing Graphical models Theoretical computer science Maximum-entropy Markov model Speech recognition N-gram Conditional random field Hidden Markov model Markov models Probability Statistics
99	DISCRIMINATIVE TRAINING OF DECODING GRAPHS FOR LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION Hong-Kwang Jeff Kuo, Brian Kingsbury Geoffrey Zweig Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2006-09-29 19:52:14 Applied mathematics Automatic identification and data capture Computer accessibility Speech recognition Science Graph Perceptron Conditional random field Hidden Markov model Computational linguistics Mathematics Neural networks
100	RECURRENT CONDITIONAL RANDOM FIELD FOR LANGUAGE UNDERSTANDING Kaisheng Yao1 , Baolin Peng1,2 , Geoffrey Zweig1 , Dong Yu1 , Xiaolong Li1 , and Feng Gao1 1 2 Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2014-05-22 12:57:20 Artificial intelligence Applied mathematics Computational neuroscience Conditional random field Theoretical computer science Recurrent neural network Information extraction Speech recognition Dynamic programming Neural networks Science Cybernetics