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#	Item
231	Mach Learn DOIs10994x Efficient inference and learning in a large knowledge base Reasoning with extracted information using a locally groundable first-order probabilistic logic Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2015-04-10 22:35:36 Link analysis Graphical models Networks Probability Mathematics PageRank Markov random field Markov logic network Artificial intelligence Theoretical computer science Applied mathematics
232	Mini-Workshop C1 From Random Walks to Particle Physics organized by: Stefan Foerste, Carsten Urbach Sun, 9::00 Add to Reading List Source URL: www.thp.uni-koeln.de Language: English - Date: 2011-10-20 07:54:27 Quantum mechanics Numerical analysis Quantum chromodynamics Monte Carlo method Quantum field theory Lattice QCD Lattice gauge theory Physics Particle physics Computational physics
233	Maximum Margin Bayesian Networks Yuhong Guo Department of Computing Science University of Alberta Add to Reading List Source URL: webdocs.cs.ualberta.ca Language: English - Date: 2005-06-06 21:14:41 Machine learning Networks Statistical models Bayesian network Markov random field Hidden Markov model Markov chain Support vector machine Supervised learning Statistics Graphical models Bayesian statistics
234	Scholarly Document Information Extraction using Extensible Features for Efficient Higher Order Semi-CRFs Nguyen Viet Cuong, Muthu Kumar Chandrasekaran, Min-Yen Kan, Wee Sun Lee∗ Department of Computer Science, National Add to Reading List Source URL: aye.comp.nus.edu.sg Language: English - Date: 2015-04-23 05:59:28 Artificial intelligence Information extraction Applied mathematics Sequence labeling Parsing Learning Machine learning Conditional random field Theoretical computer science
235	Online Large-Margin Training of Dependency Parsers Ryan McDonald Koby Crammer Fernando Pereira Department of Computer and Information Science University of Pennsylvania Add to Reading List Source URL: www.aclweb.org Language: English - Date: 2010-06-15 02:43:30 Computational linguistics Corpus linguistics Formal languages Parsing Treebank Chart parser Conditional random field Context-free grammar Perceptron Linguistics Natural language processing Compiler construction
236	ParsCit: An open-source CRF reference string parsing package Isaac G. Councill∗ , C. Lee Giles∗, Min-Yen Kan† ∗ College of Information Sciences & Technology The Pennsylvania State University Add to Reading List Source URL: aye.comp.nus.edu.sg Language: English - Date: 2010-07-06 02:40:58 Formal languages Bibliography N-gram Speech recognition Conditional random field Parsing Author citation String Citation Science Information science Library science
237	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
238	Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields Chi-Hoon Lee Department of Computing Science University of Alberta Add to Reading List Source URL: webdocs.cs.ualberta.ca Language: English - Date: 2007-06-19 18:08:48 Artificial intelligence Supervised learning Semi-supervised learning Transduction Co-training Segmentation Conditional random field Generative model Information theory Machine learning Statistics Computational statistics
239	Loopy Belief Propagation in the Presence of Determinism David Smith The University of Texas at Dallas Richardson, TX, 75080, USA Add to Reading List Source URL: www.hlt.utdallas.edu Language: English - Date: 2014-02-25 21:05:54 Probability theory Networks Statistical models Probability and statistics Mathematics Markov random field Belief propagation Bayesian network Graphical models Statistics Bayesian statistics
240	Cutset Networks: A Simple, Tractable, and Scalable Approach for Improving the Accuracy of Chow-Liu Trees Tahrima Rahman, Prasanna Kothalkar, and Vibhav Gogate Computer Science Department The University of Texas at Dallas Add to Reading List Source URL: www.hlt.utdallas.edu Language: English - Date: 2014-06-28 05:36:53 Graph theory Networks Bayesian statistics Statistical models Probability theory Bayesian network Chow-Liu tree Spanning tree Markov random field Statistics Graphical models Mathematics

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