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Mixture model
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11	S TATC MSC 35425: T OPICS IN S TATISTICAL M ACHINE L EARNING Syllabus, Spring 2016 Topics in Statistical Machine Learning is a second course in machine learning, with students assumed to have previous exposure t Add to Reading List Source URL: galton.uchicago.edu Language: English - Date: 2016-04-13 06:56:12 Statistics Machine learning Artificial intelligence Learning Statistical models Language modeling Word embedding Pattern recognition Bayesian inference Mixture model Artificial neural network Higher-order singular value decomposition
12	Scalable Training of Mixture Models via Coresets Dan Feldman MIT Matthew Faulkner Add to Reading List Source URL: eew.caltech.edu Language: English - 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
13	C:/Users/Utente/Desktop/PhD/CAL_tex/ISMIR2010_DTM/ISMIR2010_DTM.dvi Add to Reading List Source URL: eceweb.ucsd.edu Language: English - Date: 2015-07-31 19:02:39 Statistics Estimation theory Physics Mechanical engineering Cluster analysis Machine learning Mixture model Expectationmaximization algorithm Maximum likelihood estimation Work
14	Maximum Likelihood Estimation of Dirichlet Distribution Parameters Jonathan Huang Abstract. Dirichlet distributions are commonly used as priors over proportional data. In this paper, I will introduce this distribution, d Add to Reading List Source URL: jonathan-huang.org Language: English - Date: 2014-09-08 21:47:30 Statistics Mathematical analysis Probability Probability distributions Gamma distribution Dirichlet distribution Exponential family Beta distribution Mixture model Multinomial distribution Likelihood function Maximum likelihood estimation
15	2013 IEEE International Conference on Computer Vision Cosegmentation and Cosketch by Unsupervised Learning Jifeng Dai1,2 , Ying Nian Wu2 , Jie Zhou1 , and Song-Chun Zhu2 1 Department of Automation, Tsinghua University, Add to Reading List Source URL: www.stat.ucla.edu Language: English - Date: 2014-04-20 03:06:17 Image processing Statistics Artificial intelligence Image segmentation Machine learning Mixture model Template matching Market segmentation Expectationmaximization algorithm
16	A Latent Dirichlet Allocation Model for Entity Resolution Indrajit Bhattacharya Lise Getoor University of Maryland Add to Reading List Source URL: drona.csa.iisc.ernet.in Language: English - Date: 2005-12-21 17:12:02 Probability Statistics Sampling Survey methodology Mixture model Gibbs sampling Record linkage Latent Dirichlet allocation Probability distribution Prior probability Causality
17	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 53, NO. 8, AUGUSTRobust Rooftop Extraction From Visible Band Images Using Higher Order CRF Add to Reading List Source URL: peterwonka.net Language: English - Date: 2015-06-12 18:07:37 Artificial intelligence Machine learning Image segmentation Image processing Learning Vision Computer vision Region growing Conditional random field Market segmentation Mixture model Pixel
18	Correlated Community Estimation Models Over a Set of Names Suresh Veluru∗ , Yogachandran Rahulamathavan∗ , Suresh Manandhar† , and Muttukrishnan Rajarajan∗ ∗ Information Security Group, School of Engineering a Add to Reading List Source URL: www.uncertaintyofidentity.com Language: English - Date: 2014-11-25 09:34:28 Statistics Probability Probability distributions Statistical natural language processing Latent Dirichlet allocation Statistical models Mixture model Topic model Dirichlet distribution Multinomial distribution Gibbs sampling Perplexity
19	A Bayesian Approach to Learning 3D Representations of Dynamic Environments Ralf K¨astner, Nikolas Engelhard, Rudolph Triebel, and Roland Siegwart Abstract We propose a novel probabilistic approach to learning spatial re Add to Reading List Source URL: europa.informatik.uni-freiburg.de Language: English - Date: 2010-12-20 07:34:33 Statistics Statistical theory Estimation theory Bayesian statistics Statistical models Signal processing Cluster analysis Mixture model Maximum likelihood estimation Normal distribution K-means clustering Likelihood function
20	A Latent Variable Model for Geographic Lexical Variation Jacob Eisenstein Brendan O’Connor Noah A. Smith Eric P. Xing School of Computer Science Carnegie Mellon University Add to Reading List Source URL: homes.cs.washington.edu Language: English - Date: 2015-07-30 17:50:53 Statistics Probability Statistical natural language processing Probability distributions Estimation theory Regression analysis Dynamic topic model Latent Dirichlet allocation Variational Bayesian methods Mixture model Topic model Normal distribution