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Markov random field
Results: 325

#	Item
31	Budgeted Online Collective Inference Jay Pujara University of Maryland Add to Reading List Source URL: psl.umiacs.umd.edu Language: English - Date: 2015-07-31 17:33:33 Graphical models Statistical theory Probability theory Statistical models Bayesian inference Statistical inference Bayesian network Markov random field Belief propagation Scala First-order logic Loss function
32	Extracting Route Directions from Web Pages Xiao Zhang! , Prasenjit Mitra!† , Sen Xu‡ , Anuj R. Jaiswal† , Alex Klippel‡ , Alan MacEachren‡ ! Department of Computer Science and Engineering Add to Reading List Source URL: webdb09.cse.buffalo.edu Language: English - Date: 2009-06-24 13:24:22 Natural language processing Machine learning Markov models Computational linguistics Data mining Information extraction Part-of-speech tagging Search engine indexing Conditional random field Speech recognition Sentence Bag-of-words model
33	Learning Conditional Random Fields for Stereo Daniel Scharstein Middlebury College Middlebury, VT, USA Chris Pal Add to Reading List Source URL: www.cs.middlebury.edu Language: English - Date: 2007-06-15 21:08:12 Machine learning Graphical models Conditional random field Stereoscopy Vision Image segmentation Markov random field Mixture model Supervised learning Stereopsis Regression analysis
34	Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction Stephen H. Bach Bert Huang Add to Reading List Source URL: psl.umiacs.umd.edu Language: English - Date: 2013-11-10 21:52:40 Graphical models Markov models Probability theory Markov random field Structured prediction Bayesian network Random field Markov chain Support vector machine Markov logic network Algorithm Hidden Markov model
35	OFFPRINT How rare are diffusive rare events? D. P. Sanders and H. Larralde EPL, Add to Reading List Source URL: sistemas.fciencias.unam.mx Language: English - Date: 2011-03-31 15:04:54 Statistical mechanics Stochastic processes Brownian motion Random walk Ergodic theory Markov chain Mean field theory De BroglieBohm theory
36	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
37	Microsoft PowerPoint - class-5-out.ppt [Compatibility Mode] Add to Reading List Source URL: people.cs.pitt.edu Language: English - Date: 2014-09-09 17:58:53 Graphical models Probability theory Belief propagation Coding theory Markov random field Factor graph Variable elimination Tree decomposition Logarithm Centrality
38	Learning Minimal Latent Directed Information Trees Add to Reading List Source URL: coleman.ucsd.edu Language: English Graphical models Probability theory Statistical models Graph theory Markov random field Binary tree Graph
39	Combining Discriminative Features to Infer Complex Trajectories David A. Ross Simon Osindero Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2006-06-07 15:00:45 Machine learning Robot control Markov models Estimation theory Kalman filter Pattern recognition Conditional random field Video tracking Causality Optical flow Particle filter