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Random field
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#	Item
41	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
42	Department Logo & Letterhead PRESS RELEASE For Immediate Release [Date] Add to Reading List Source URL: www.ots.ca.gov Language: English - Date: 2015-10-19 19:49:58 Driving under the influence Alcohol Law Drunk driving in the United States Misconduct Designated driver Drunk drivers Road traffic safety Impaired driving in Canada Random checkpoint Field sobriety testing
43	FACULTY: FIELD OF STUDY: COURSE TITLE: LECTURER’S NAME: E-MAIL ADDRESS OF THE LECTURER: ECTS POINTS FOR THE COURSE: Add to Reading List Source URL: wtie.tu.koszalin.pl Language: English - Date: 2015-03-03 06:15:34 Probability theory Probability Mathematical analysis Statistical theory Statistics Murray R. Spiegel Probability distribution Probability density function Randomness Mathematical statistics Seymour Lipschutz Random variable
44	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
45	A Conditional Random Field for Multiple-Instance Learning Thomas Deselaers Vittorio Ferrari Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland Add to Reading List Source URL: thomas.deselaers.de Language: English - Date: 2014-10-11 09:29:28 Machine learning Learning Artificial intelligence Multiple instance learning Multiple-instance learning Support vector machine Conditional random field Bag Semi-supervised learning Statistical classification
46	IITP: Hybrid Approach for Text Normalization in Twitter Md Shad Akhtar, Utpal Kumar Sikdar and Asif Ekbal Dept of Computer Science and Engineering IIT Patna Patna, India (shad.pcs15,utpal.sikdar,asif)@iitp.ac.in Add to Reading List Source URL: noisy-text.github.io Language: English - Date: 2016-08-14 21:11:08 Computational linguistics Software Computing Artificial intelligence Named-entity recognition Normalization Stemming Conditional random field Twitter Database normalization Machine translation
47	Multi-Class Object Localization by Combining Local Contextual Interactions Carolina Galleguillos† Brian McFee† Serge Belongie† Gert Lanckriet‡ † Computer Science and Engineering Department Add to Reading List Source URL: eceweb.ucsd.edu Language: English - Date: 2015-07-31 19:00:26 Machine learning Learning Artificial intelligence Statistical classification Image processing Data mining Multiple kernel learning Image segmentation Kernel K-nearest neighbors algorithm Conditional random field Outline of object recognition
48	CRF-Based Authors’ Name Tagging for Scanned Documents Add to Reading List Source URL: www.jcdl2008.org Language: English - Date: 2008-07-30 15:15:44 Artificial intelligence Computing Information science Computational linguistics Delimiter Pattern matching String Conditional random field Optical character recognition Tag
49	Low Level Vision via Switchable Markov Random Fields Dahua Lin CSAIL, MIT John Fisher CSAIL, MIT Add to Reading List Source URL: dahua.me Language: English - Date: 2013-01-06 22:24:23 Statistics Artificial intelligence Computer vision Graphical models Machine learning Image processing Image segmentation Bayesian statistics Markov random field Conference on Computer Vision and Pattern Recognition Mixture model Noise reduction
50	Learning Latent Groups with Hinge-loss Markov Random Fields Stephen H. Bach Bert Huang Lise Getoor University of Maryland, College Park, Maryland 20742, USA Add to Reading List Source URL: stephenbach.net Language: English - Date: 2013-06-14 15:37:03 Statistics Probability theory Graphical models Machine learning Statistical models Statistical theory Bayesian statistics Markov random field Latent variable Expectationmaximization algorithm Marginal likelihood Conditional random field

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