NIPS
2001
14 years 27 days 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
14 years 27 days 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
15 years 10 days ago
2006
IEEE
ICIP
2007
IEEE
15 years 1 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
15 years 1 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...