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Hidden semi-Markov model
Results: 21

#	Item
1	DETECTING UNSAFE DRIVING PATTERNS USING DISCRIMINATIVE LEARNING Yue Zhou†, Wei Xu‡, Huazhong Ning†, Yihong Gong‡, Thomas S. Huang† †Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL 61 Add to Reading List Source URL: www.ifp.illinois.edu Language: English - Date: 2008-05-05 15:25:20 Machine learning Conditional random field Pattern recognition Supervised learning Hidden Markov model Support vector machine Semi-supervised learning Expectationmaximization algorithm Mixture model Artificial neural network Viterbi algorithm
2	An Evaluation of Models for Predicting Opponent Positions in First-Person Shooter Video Games Stephen Hladky and Vadim Bulitko filters to predict opponent positions in first-person shooter (FPS) video games. These models Add to Reading List Source URL: www.csse.uwa.edu.au Language: English - Date: 2009-02-05 01:17:42 Statistics Monte Carlo methods Probability theory Estimation theory Robot control Nonparametric statistics Markov models Particle filter Prediction Hidden semi-Markov model Resampling Markov chain
3	Semi-Supervised Sequence Labeling with Self-Learned Features Yanjun Qi∗ , Pavel Kuksa† , Ronan Collobert∗ , Kunihiko Sadamasa∗ , Koray Kavukcuoglu‡ and Jason Weston§ ∗ Machine Learning Department, NEC Labs A Add to Reading List Source URL: ronan.collobert.com Language: English - Date: 2009-09-30 13:22:00 Science Semi-supervised learning Natural language processing Co-training Supervised learning Sequence labeling Part-of-speech tagging Conditional random field Hidden Markov model Machine learning Artificial intelligence Statistics
4	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
5	c 2004 by Kevin Michael Squire. All rights reserved. HMM-BASED SEMANTIC LEARNING FOR A MOBILE ROBOT BY Add to Reading List Source URL: www.isle.illinois.edu Language: English - Date: 2005-05-13 18:11:18 Applied mathematics Bioinformatics Computational linguistics Models of computation Hidden Markov model Speech recognition Artificial neural network Markov chain Hidden semi-Markov model Markov models Statistics Machine learning
6	Discriminative Unsupervised Learning of Structured Predictors Linli Xu Dana Wilkinson Add to Reading List Source URL: webdocs.cs.ualberta.ca Language: English - Date: 2006-05-10 00:01:14 Statistics Hidden Markov model Conditional random field Support vector machine Supervised learning Discriminative model Convex optimization Semi-supervised learning Markov random field Machine learning Mathematics Algebra
7	MAXIMUM-LIKELIHOOD ADAPTATION OF SEMI-CONTINUOUS HMMS BY LATENT VARIABLE DECOMPOSITION OF STATE DISTRIBUTIONS Antoine Raux and Rita Singh School of Computer Science, Carnegie Mellon University, USA {antoine, rsingh}@cs.c Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2004-07-30 13:47:46 Markov models Estimation theory Bioinformatics Hidden Markov model Statistical models Probabilistic latent semantic analysis Expectation–maximization algorithm Mixture model Singular value decomposition Statistics Algebra Mathematics
8	Elsevier Editorial System(tm) for Pervasive and Mobile Computing Manuscript Draft Manuscript Number: PMC-D-08-00114R2 Title: Wearable-Sensor Activity Analysis Using Semi-Markov Models with a Grammar. Article Type: Resear Add to Reading List Source URL: www2.mta.ac.il Language: English - Date: 2009-12-16 18:15:39 Expectation–maximization algorithm Segmentation Markov chain Support vector machine Tree Statistics Markov models Hidden Markov model
9	Recognizing Activities in Multiple Contexts using Transfer Learning T.L.M. van Kasteren and G. Englebienne and B.J.A. Kr¨ose Intelligent Systems Lab Amsterdam (ISLA) Science Park, Kruislaan 403, 1098 SJ Amsterdam, The N Add to Reading List Source URL: www.aaai.org Language: English - Date: 2008-10-15 16:33:56 Markov models Estimation theory Statistical theory Expectation–maximization algorithm Activity recognition Hidden Markov model Maximum likelihood Semi-supervised learning Pattern recognition Statistics Machine learning Artificial intelligence
10	Semi-Markov Conditional Random Fields for Information Extraction Sunita Sarawagi Indian Institute of Technology Bombay, India [removed] Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2004-06-07 09:08:44 Graphical models Theoretical computer science Applied mathematics Markov processes Machine learning Conditional random field Markov chain Perceptron Hidden Markov model Statistics Markov models Science

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