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» An Efficient Approach to Learning Inhomogeneous Gibbs Model
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CVPR
2003
IEEE
14 years 7 months ago
An Efficient Approach to Learning Inhomogeneous Gibbs Model
Inhomogeneous Gibbs model (IGM) [4] is an effective maximum entropy model in characterizing complex highdimensional distributions. However, its training process is so slow that th...
Ziqiang Liu, Hong Chen, Heung-Yeung Shum
ICCV
2001
IEEE
14 years 7 months ago
Learning Inhomogeneous Gibbs Model of Faces by Minimax Entropy
In this paper we propose a novel inhomogeneous Gibbs model by the minimax entropy principle, and apply it to face modeling. The maximum entropy principle generalizes the statistic...
Ce Liu, Song Chun Zhu, Heung-Yeung Shum
ICML
2007
IEEE
14 years 6 months ago
A permutation-augmented sampler for DP mixture models
We introduce a new inference algorithm for Dirichlet process mixture models. While Gibbs sampling and variational methods focus on local moves, the new algorithm makes more global...
Percy Liang, Michael I. Jordan, Benjamin Taskar
AUTOMATICA
2006
122views more  AUTOMATICA 2006»
13 years 5 months ago
Gibbs sampler-based coordination of autonomous swarms
In this paper a novel, Gibbs sampler-based algorithm is proposed for coordination of autonomous swarms. The swarm is modeled as a Markov random field (MRF) on a graph with a time-...
Wei Xi, Xiaobo Tan, John S. Baras
CVPR
2004
IEEE
14 years 7 months ago
Gibbs Likelihoods for Bayesian Tracking
Bayesian methods for visual tracking model the likelihood of image measurements conditioned on a tracking hypothesis. Image measurements may, for example, correspond to various fi...
Stefan Roth, Leonid Sigal, Michael J. Black