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ICPR
2008
IEEE
14 years 4 months ago
A variational inference based approach for image segmentation
In this paper, we present a variational Bayes (VB) approach for image segmentation. First, image is modeled by a mixture model, and then with the techniques of factor analyzer, th...
Zhenglong Li, Qingshan Liu, Jian Cheng, Hanqing Lu
SDM
2007
SIAM
187views Data Mining» more  SDM 2007»
13 years 11 months ago
Topic Models over Text Streams: A Study of Batch and Online Unsupervised Learning
Topic modeling techniques have widespread use in text data mining applications. Some applications use batch models, which perform clustering on the document collection in aggregat...
Arindam Banerjee, Sugato Basu
ACL
2006
13 years 11 months ago
BiTAM: Bilingual Topic AdMixture Models for Word Alignment
We propose a novel bilingual topical admixture (BiTAM) formalism for word alignment in statistical machine translation. Under this formalism, the parallel sentence-pairs within a ...
Bing Zhao, Eric P. Xing
NIPS
2008
13 years 11 months ago
Syntactic Topic Models
We develop the syntactic topic model (STM), a nonparametric Bayesian model of parsed documents. The STM generates words that are both thematically and syntactically constrained, w...
Jordan L. Boyd-Graber, David M. Blei
PKDD
2010
Springer
184views Data Mining» more  PKDD 2010»
13 years 8 months ago
Shift-Invariant Grouped Multi-task Learning for Gaussian Processes
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
Yuyang Wang, Roni Khardon, Pavlos Protopapas