NIPS
2001
13 years 7 months ago
2001
We show that it is possible to extend hidden Markov models to have a countably infinite number of hidden states. By using the theory of Dirichlet processes we can implicitly integ...
NIPS
2004
13 years 7 months ago
2004
We propose the hierarchical Dirichlet process (HDP), a nonparametric Bayesian model for clustering problems involving multiple groups of data. Each group of data is modeled with a...
ICML
2006
IEEE
14 years 6 months ago
2006
IEEE
ICIP
2007
IEEE
14 years 7 months ago
2007
IEEE
We develop a hierarchical, nonparametric statistical model for wavelet representations of natural images. Extending previous work on Gaussian scale mixtures, wavelet coefficients ...
CVPR
2007
IEEE
14 years 7 months ago
2007
IEEE
We propose a novel unsupervised learning framework for activity perception. To understand activities in complicated scenes from visual data, we propose a hierarchical Bayesian mod...