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Graphical models
Results: 1083

#	Item
41	Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction Stephen H. Bach Bert Huang Add to Reading List Source URL: stephenbach.net Language: English - Date: 2013-11-10 21:50:33 Machine learning Graphical models Probability Statistics Markov models Probability theory Markov random field Structured prediction Bayesian network Random field Support vector machine Markov chain
42	ABSTRACT Title of dissertation: HINGE-LOSS MARKOV RANDOM FIELDS AND PROBABILISTIC SOFT LOGIC: Add to Reading List Source URL: stephenbach.net Language: English - Date: 2015-10-08 14:59:19 Statistics Machine learning Probability Statistical models Graphical models Bayesian statistics Markov networks Statistical relational learning Probabilistic soft logic Markov random field Structured prediction Expectationmaximization algorithm
43	Attend, Infer, Repeat: Fast Scene Understanding with Deep Generative Models S. M. Ali Eslami David Szepesvari Add to Reading List Source URL: juxi.net Language: English - Date: 2016-06-17 11:44:38 Artificial neural networks Statistics Artificial intelligence Applied mathematics Cybernetics Computational neuroscience Computational statistics Deep learning Graphical models Bayesian network Pattern recognition Computer vision
44	Univ. of Pittsburgh Conditional Random Fields Add to Reading List Source URL: people.cs.pitt.edu Language: English - Date: 2014-10-25 10:56:22 Graphical models Machine learning Statistical models Learning Artificial intelligence Statistics Conditional random field Generative model Markov random field Discriminative model Bayesian network Factor graph
45	Course Syllabus: COMPSCI 688 Probabilistic Graphical Models – Spring 2016 Instructor: Prof. Brendan O’Connor (http://brenocon.com) Add to Reading List Source URL: people.cs.umass.edu Language: English - Date: 2016-02-29 18:06:04 Statistics Education Applied mathematics Computational statistics Statistical models Graphical models Bayesian statistics Markov models Bayesian network Markov random field Educational technology Markov chain Monte Carlo
46	Efficient Information-Theoretic Graph Pruning for Graph-Based SLAM with Laser Range Finders Henrik Kretzschmar Cyrill Stachniss Add to Reading List Source URL: europa.informatik.uni-freiburg.de Language: English - Date: 2011-09-06 03:42:53 Graph theory Mathematics Combinatorial optimization Statistical models Robot navigation Simultaneous localization and mapping Matching Line graph Graphical model Graph
47	Learning Articulated Skeletons from Motion David A. Ross, Daniel Tarlow, and Richard S. Zemel Department of Computer Science, University of Toronto, Canada {dross,dtarlow,zemel}@cs.toronto.edu Abstract. Humans demonstra Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2007-08-14 20:36:06 Statistics Statistical models Mathematics Graph theory Dynamical systems Mechanics Spanning tree Structure from motion Multibody system Image segmentation Bayesian network Graphical model
48	Marginals-to-Models Reducibility Michael Kearns University of Pennsylvania Add to Reading List Source URL: theory.stanford.edu Language: English - Date: 2013-11-08 17:46:03 Mathematics Computational complexity theory Graph theory Graphical models Combinatorial optimization Convex optimization Operations research Probability theory Polynomial Ellipsoid method Markov random field Bayesian network
49	Probabilistic Message Passing in Peer Data Management Systems∗ Philippe Cudr´e-Mauroux School of Computer and Communication Sciences EPFL – Switzerland Add to Reading List Source URL: lsirpeople.epfl.ch Language: English - Date: 2006-01-25 04:01:26 Information science Ontology Semantic Web Information Graphical models Computing Databases Schema matching Data integration Data model Ontology alignment Belief propagation

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