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Sequence labeling
Results: 43

#	Item
11	Conditional Random Fields with High-Order Features for Sequence Labeling Dan Wu Hai Leong Chieu Nan Ye Add to Reading List Source URL: www.comp.nus.edu.sg Language: English - Date: 2013-03-09 06:31:30 Probability and statistics Machine learning Conditional random field Theoretical computer science Markov chain Hidden Markov model Bayesian network Statistics Markov models Graphical models
12	Semi-Markov Conditional Random Field with High-Order Features Viet Cuong Nguyen Nan Ye Wee Sun Lee National University of Singapore Add to Reading List Source URL: www.comp.nus.edu.sg Language: English - Date: 2013-03-09 06:33:11 Theoretical computer science Statistics Learning Applied mathematics Hidden Markov model Sequence labeling Machine learning Markov models Conditional random field
13	Active Learning for Probabilistic Hypotheses Using the Maximum Gibbs Error Criterion Nguyen Viet Cuong Wee Sun Lee Nan Ye Department of Computer Science Add to Reading List Source URL: www.comp.nus.edu.sg Language: English - Date: 2013-12-27 04:21:58 Information theory Cybernetics Statistical inference Gibbs sampling Entropy Estimation theory Sequence labeling Statistics Machine learning Statistical theory
14	Supplementary Material for “Conditional Random Fields with High-Order Features for Sequence Labeling” Dan Wu Singapore MIT Alliance Add to Reading List Source URL: www.comp.nus.edu.sg Language: English - Date: 2010-03-02 00:50:33
15	Journal of Machine Learning Research1009 Submitted 10/12; Revised 9/13; Published 3/14 Conditional Random Field with High-order Dependencies for Sequence Labeling and Segmentation Add to Reading List Source URL: www.comp.nus.edu.sg Language: English - Date: 2014-08-21 10:57:11 Statistics Applied mathematics Probability Graphical models Conditional random field Hidden Markov model Segmentation Algorithm Normal distribution Markov models Machine learning Theoretical computer science
16	Active Learning for Probabilistic Hypotheses Using the Maximum Gibbs Error Criterion Nguyen Viet Cuong Wee Sun Lee Nan Ye Department of Computer Science Add to Reading List Source URL: www.comp.nus.edu.sg Language: English - Date: 2014-05-28 05:12:50 Information theory Cybernetics Statistical inference Gibbs sampling Entropy Estimation theory Sequence labeling Statistics Machine learning Statistical theory
17	Journal of Machine Learning Research1009 Submitted 10/12; Revised 9/13; Published 3/14 Conditional Random Field with High-order Dependencies for Sequence Labeling and Segmentation Add to Reading List Source URL: www.comp.nus.edu.sg Language: English - Date: 2014-07-04 08:25:36 Statistics Applied mathematics Probability Graphical models Conditional random field Hidden Markov model Segmentation Algorithm Normal distribution Markov models Machine learning Theoretical computer science
18	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
19	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
20	Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling Feng Jiao University of Waterloo Abstract We present a new semi-supervised training Add to Reading List Source URL: webdocs.cs.ualberta.ca Language: English - Date: 2006-12-28 15:24:48 Statistical theory Estimation theory Conditional random field Theoretical computer science Supervised learning Kullback–Leibler divergence Semi-supervised learning Expectation–maximization algorithm Conditional entropy Statistics Machine learning Information theory

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