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Mixture model
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#	Item
151	A Conditional Multinomial Mixture Model for Superset Label Learning (Supplementary Materials) Thomas G. Dietterich EECS, Oregon State University Corvallis, OR 97331 Add to Reading List Source URL: web.engr.oregonstate.edu Language: English - Date: 2012-11-14 14:44:30
152	Influence-based Network-oblivious Community Detection Nicola Barbieri Yahoo Labs, Barcelona, Spain Add to Reading List Source URL: www.francescobonchi.com Language: English - Date: 2013-10-23 04:36:36 Estimation theory Statistical models Gamma distribution Maximum likelihood estimation Mixture model Expectationmaximization algorithm
153	Variational Inference with Normalizing Flows Danilo Jimenez Rezende Shakir Mohamed Google DeepMind, London Add to Reading List Source URL: jmlr.org Language: English - Date: 2015-09-16 19:38:47 Statistics Probability Statistical models Graphical models Probability distributions Variational Bayesian methods Bayesian network Expectationmaximization algorithm Normal distribution Mixture model Exponential family Bayesian inference
154	Auxiliary Variables in Mixture Modeling: Using the BCH Method in Mplus to Estimate a Distal Outcome Model and an Arbitrary Secondary Model Tihomir Asparouhov and Bengt Muth´en Mplus Web Notes: No. 21 Add to Reading List Source URL: www.statmodel.com Language: English - Date: 2014-10-07 15:21:11
155	Image and Vision Computing–97 www.elsevier.com/locate/imavis An observation-constrained generative approach for probabilistic classification of image regions Sanjiv Kumara,, Alexander C. Louib, Martial He Add to Reading List Source URL: www.sanjivk.com Language: English* - Date: 2010-06-01 18:50:17 Probability and statistics Segmentation Generative model Mixture model Minimum description length Unsupervised learning Expectation–maximization algorithm Statistical classification Supervised learning Machine learning Statistics Computational statistics
156	Remote Sensing of Environment – 77 www.elsevier.com/locate/rse On the choice of spatial and categorical scale in remote sensing land cover classification Junchang Jua,T, Sucharita Gopala, Eric D. Kolaczykb Add to Reading List Source URL: people.bu.edu Language: English - Date: 2007-10-09 09:57:54 Probability and statistics Geography Segmentation Remote sensing Map Level of measurement Mixture model Scale model Statistics Cartography Image processing
157	Parametric Herding Yutian Chen Max Welling Bren School of Information and Computer Science University of California, Irvine Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2010-03-16 13:28:39 Machine learning Econometrics M-estimators Regression analysis Mixture model Maximum likelihood Boltzmann machine Expectation–maximization algorithm Vector quantization Statistics Estimation theory Statistical theory
158	Randomized Algorithms for Fast Bayesian Hierarchical Clustering Katherine A. Heller and Zoubin Ghahramani Gatsby Computational Neuroscience Unit University College London, London, WC1N 3AR, UK {heller,zoubin}@gatsby.ucl. Add to Reading List Source URL: www.gatsby.ucl.ac.uk Language: English - Date: 2005-10-18 12:07:50 Data mining Geostatistics Hierarchical clustering Mixture model Unsupervised learning Randomized algorithm Data stream clustering Consensus clustering Statistics Machine learning Cluster analysis
159	Exchangeable Inconsistent Priors for Bayesian Posterior Inference Max Welling Ian Porteous Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2012-02-01 15:33:24 Dirichlet process Poisson distribution Principle of maximum entropy Prior probability Normal distribution Mixture model Gibbs sampling Empirical Bayes method Bayesian inference Statistics Probability and statistics Bayesian statistics
160	Incremental Learning of Nonparametric Bayesian Mixture Models Ryan Gomes∗ Max Welling† ∗ Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2008-04-09 01:39:03 Cluster analysis Data analysis Estimation theory Expectation–maximization algorithm Dirichlet process Variational Bayesian methods Mixture model Principal component analysis Kernel principal component analysis Statistics Multivariate statistics Machine learning

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