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Bayesian network
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#	Item
971	Efficient discriminative learning of Bayesian network classifier via Boosted Augmented Naive Bayes Yushi Jing College of Computing, Georgia Institute of Technology, Atlanta, GA[removed]USA Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:15:42 Statistical classification Statistical models Naive Bayes classifier Ensemble learning Bayesian inference Bayesian network Computational learning theory Averaged one-dependence estimators AdaBoost Statistics Bayesian statistics Machine learning
972	Learning Class-Discriminative Dynamic Bayesian Networks John Burge Terran Lane Department of Computer Science, University of New Mexico Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:15:43 Statistical models Statistical classification Graphical models Bayesian network Maximum likelihood Naive Bayes classifier Speech recognition Kullback–Leibler divergence Bayesian inference Statistics Bayesian statistics Statistical theory
973	SEA ICE PREDICTION NETWORK (SIPN) Template for Pan-Arctic Sea Ice Outlook Core Contributions June Report (Using May Data) Add to Reading List Source URL: www.arcus.org Language: English - Date: 2014-07-17 16:53:54 Scientific method Interpolation Statistical theory Econometrics Regression analysis Prediction Extrapolation Bayesian inference Kriging Statistics Science Statistical inference
974	IRIT at TREC Microblog 2012: Adhoc Task Lamjed Ben Jabeur, Firas Damak, Lynda Tamine, Karen Pinel-Sauvagnat, Guillaume Cabanac, and Mohand Boughanem {jabeur, damak, tamine, cabanac, sauvagnat, boughanem}@irit.fr, IRIT/SI Add to Reading List Source URL: trec.nist.gov Language: English - Date: 2013-02-12 08:11:19 Information Twitter Learning to rank Text Retrieval Conference Relevance Query expansion Bayesian network Tf*idf Naive Bayes classifier Information science Information retrieval Science
975	David M. Blei Princeton University Department of Computer Science 35 Olden Street Princeton, NJ 08540 Add to Reading List Source URL: www.cs.princeton.edu Language: English - Date: 2014-04-06 15:27:19 Dynamic topic model Latent Dirichlet allocation Pachinko allocation Machine learning Dirichlet process Neural network Bayesian inference Mixture model Variational Bayesian methods Statistics Statistical natural language processing Topic model
976	Scalable Inference in Latent Variable Models ∗ Amr Ahmed, Mohamed Aly, Joseph Gonzalez, Shravan Narayanamurthy, Alexander Smola Yahoo! Research, Santa Clara, CA, USA Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2012-03-26 21:38:12 Latent variable Gibbs sampling Latent Dirichlet allocation Bayesian network Mixture model Variable Parallel computing Latent class model Variational Bayesian methods Statistics Statistical models Latent variable model
977	SEA ICE PREDICTION NETWORK (SIPN) Template for Pan-Arctic Sea Ice Outlook Core Contributions June Report (Using May Data) Add to Reading List Source URL: www.arcus.org Language: English - Date: 2014-06-16 20:25:59 Scientific method Interpolation Statistical theory Econometrics Regression analysis Prediction Extrapolation Bayesian inference Kriging Statistics Science Statistical inference
978	Article should be cited as: Amstrup, S. C. , B. G. Marcot, and D. C. Douglas[removed]A Bayesian Network Modeling Approach to Forecasting the 21st Century Worldwide Status of Polar Bears. Pages[removed]In Eric. T. DeWeaver Add to Reading List Source URL: alaska.usgs.gov Language: English - Date: 2014-08-07 14:34:06 Glaciology Sea ice Bears Arctic Ocean Poles Polar bear Polar ice packs Global climate model Brown bear Physical geography Earth Zoology
979	THIS IS A DRAFT VERSION. FINAL VERSION TO BE PUBLISHED AT NIPS ’06 A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation Yee Whye Teh Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2008-10-31 18:54:20 Statistical models Graphical models Variational Bayesian methods Latent Dirichlet allocation Gibbs sampling Bayesian network Normal distribution Marginal likelihood Mixture model Statistics Bayesian statistics Probability and statistics
980	GENERAL FRAMEWORK FOR MIXED GRAPHICAL MODELS Yulia Baker Departments of Statistics and Electrical & Computer Engineering, Rice University, Department of Pediatrics-Neurology, Baylor College of Medicine, & Jan and Dan Dun Add to Reading List Source URL: srcos2014.blogs.rice.edu Language: English - Date: 2014-07-30 17:09:37 Statistics Theoretical computer science Statistical models Bayesian statistics Conditional random field Markov random field Mutation P53 Gene regulatory network Biology Graphical models Networks

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