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ICML
2008
IEEE
16 years 7 months ago
An HDP-HMM for systems with state persistence
The hierarchical Dirichlet process hidden Markov model (HDP-HMM) is a flexible, nonparametric model which allows state spaces of unknown size to be learned from data. We demonstra...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
ICML
2004
IEEE
16 years 7 months ago
Approximate inference by Markov chains on union spaces
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
Max Welling, Michal Rosen-Zvi, Yee Whye Teh
CHI
2004
ACM
16 years 6 months ago
Acquiring in situ training data for context-aware ubiquitous computing applications
Ubiquitous, context-aware computer systems may ultimately enable computer applications that naturally and usefully respond to a user's everyday activity. Although new algorit...
Stephen S. Intille, Ling Bao, Emmanuel Munguia Tap...
ICIAP
2003
ACM
16 years 6 months ago
A topological approach for segmenting human body shape
Segmentation of 3D human body is a very challenging problem in applications exploiting human scan data. To tackle this problem, this paper proposes a topological approach based on...
Yijun Xiao, Naoufel Werghi, Paul Siebert
SDM
2009
SIAM
220views Data Mining» more  SDM 2009»
16 years 3 months ago
Bayesian Cluster Ensembles.
Cluster ensembles provide a framework for combining multiple base clusterings of a dataset to generate a stable and robust consensus clustering. There are important variants of th...
Hongjun Wang, Hanhuai Shan, Arindam Banerjee