79 search results - page 4 / 16 » Structure Learning with Nonparametric Decomposable Models |
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Policy gradient approaches are a powerful instrument for learning how to interact with the environment. Existing approaches have focused on propositional and continuous domains on...
EMNLP
2008
13 years 9 months ago
2008
We describe the first tractable Gibbs sampling procedure for estimating phrase pair frequencies under a probabilistic model of phrase alignment. We propose and evaluate two nonpar...
CVPR
2012
IEEE
11 years 10 months ago
2012
IEEE
Pictorial Structures (PS) define a probabilistic model of 2D articulated objects in images. Typical PS models assume an object can be represented by a set of rigid parts connecte...
JMLR
2010
13 years 2 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...
ECML
2007
Springer
14 years 2 months ago
2007
Springer
Abstract. Clustering has recently enjoyed progress via spectral methods which group data using only pairwise affinities and avoid parametric assumptions. While spectral clustering ...