Scalable Training of Mixture Models via Coresets Dan Feldman MIT Matthew Faulkner

First Page		Document Content
Date: 2012-05-15 11:47:37 Statistics Probability Maximum likelihood estimation Probability distributions Bayesian statistics Expectationmaximization algorithm Mixture model Normal distribution K-means clustering Likelihood function Data stream clustering Gamma distribution		Scalable Training of Mixture Models via Coresets Dan Feldman MIT Matthew Faulkner Add to Reading List Source URL: eew.caltech.edu Download Document from Source Website File Size: 777,95 KB Share Document on Facebook

	POLS 506: Advanced Topics in Political Methodology Bayesian Statistics 211 Herzstein Hall, Thursday 2:30p-5:20p Dr. Justin Esarey Associate Professor of Political Science DocID: 1vhuw - View Document
	Bayesian item response modeling: an application for universities admission tests Javier Mart´ınez. Scientific Computing & Statistics Dept., Universidad Sim´on Bol´ıvar, Venezuela. DocID: 1vamk - View Document
	Graham Neubig – Non-parametric Bayesian Statistics Non-parametric Bayesian Statistics Graham Neubig DocID: 1uQOM - View Document
	Bayesian non-Gaussian state space models in R Random-walk Metropolis versus Hamiltonian Monte Carlo Jouni Helske University of Jyv¨askyl¨a, Department of Mathematics and Statistics DocID: 1uLQw - View Document
	Recap .... Bayesian Statistics ....... DocID: 1uHaX - View Document