116 search results - page 15 / 24 » Monte Carlo Hierarchical Model Learning |
92
Voted
NIPS
2000
15 years 1 months ago
2000
Recent work has exploited boundedness of data in the unsupervised learning of new types of generative model. For nonnegative data it was recently shown that the maximum-entropy ge...
CVPR
2003
IEEE
16 years 2 months ago
2003
IEEE
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...
111
Voted
AMDO
2006
Springer
15 years 4 months ago
2006
Springer
This paper considers the problem of monocular human body tracking using learned models. We propose to learn the joint probability distribution of appearance and body pose using a m...
115
Voted
UAI
2004
15 years 1 months ago
2004
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
121
Voted
JMLR
2010
14 years 7 months ago
2010
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...