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» Model-Based Motion Clustering Using Boosted Mixture Modeling
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ICCV
2007
IEEE
13 years 11 months ago
Two-View Motion Segmentation by Mixtures of Dirichlet Process with Model Selection and Outlier Removal
This paper presents a novel motion segmentation algorithm on the basis of mixture of Dirichlet process (MDP) models, a kind of nonparametric Bayesian framework. In contrast to pre...
Yong-Dian Jian, Chu-Song Chen
ICIP
2001
IEEE
14 years 7 months ago
Minimum discrimination information clustering: modeling and quantization with Gauss mixtures
Gauss mixtures have gained popularity in statistics and statistical signal processing applications for a variety of reasons, including their ability to well approximatea large cla...
Robert M. Gray, John C. Young, Anuradha K. Aiyer
ICASSP
2008
IEEE
13 years 11 months ago
Unsupervised language model adaptation via topic modeling based on named entity hypotheses
Language model (LM) adaptation is often achieved by combining a generic LM with a topic-specific model that is more relevant to the target document. Unlike previous work on unsup...
Yang Liu, Feifan Liu
CVPR
2005
IEEE
14 years 7 months ago
Subspace Analysis Using Random Mixture Models
In [1], three popular subspace face recognition methods, PCA, Bayes, and LDA were analyzed under the same framework and an unified subspace analysis was proposed. However, since t...
Xiaogang Wang, Xiaoou Tang
ICDM
2003
IEEE
134views Data Mining» more  ICDM 2003»
13 years 10 months ago
Probabilistic User Behavior Models
We present a mixture model based approach for learning individualized behavior models for the Web users. We investigate the use of maximum entropy and Markov mixture models for ge...
Eren Manavoglu, Dmitry Pavlov, C. Lee Giles