Spatial distance dependent Chinese restaurant processes for image segmentation Soumya Ghosh1 , Andrei B. Ungureanu2 , Erik B. Sudderth1 , and David M. Blei3 1 Department of Computer Science, Brown University, {sghosh,su

First Page		Document Content
Date: 2015-03-12 00:16:21 Cluster analysis Image processing Segmentation Market segmentation Dirichlet process K-means clustering Mixture model Chinese restaurant process Spectral clustering Statistics Stochastic processes Machine learning		Spatial distance dependent Chinese restaurant processes for image segmentation Soumya Ghosh1 , Andrei B. Ungureanu2 , Erik B. Sudderth1 , and David M. Blei3 1 Department of Computer Science, Brown University, {sghosh,su Add to Reading List Source URL: www.cs.columbia.edu Download Document from Source Website File Size: 1,81 MB Share Document on Facebook

	Newton Method for the ICA Mixture Model DocID: 1vftd - View Document
	Semi-Supervised Learning with the Deep Rendering Mixture Model Tan Nguyen1,2 Wanjia Liu1 Ethan Perez1 Richard G. Baraniuk1 DocID: 1v26R - View Document
	BUDVYTIS ET AL.: MOT FOR VIDEO SEGMENTATION 1 MoT - Mixture of Trees Probabilistic Graphical Model for Video Segmentation DocID: 1uILx - View Document
	Vol. 18 noPages 1194–1206 BIOINFORMATICS Bayesian infinite mixture model based clustering DocID: 1usTr - View Document
	Research © 2011 by The American Society for Biochemistry and Molecular Biology, Inc. This paper is available on line at http://www.mcponline.org A Bayesian Mixture Model for Comparative Spectral Count Data in Shotgun Pr DocID: 1uaWx - View Document