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ICANN
2007
Springer
14 years 1 months ago
Structure Learning with Nonparametric Decomposable Models
Abstract. We present a novel approach to structure learning for graphical models. By using nonparametric estimates to model clique densities in decomposable models, both discrete a...
Anton Schwaighofer, Mathäus Dejori, Volker Tr...
CVPR
2005
IEEE
14 years 9 months ago
Mixture Trees for Modeling and Fast Conditional Sampling with Applications in Vision and Graphics
We introduce mixture trees, a tree-based data-structure for modeling joint probability densities using a greedy hierarchical density estimation scheme. We show that the mixture tr...
Frank Dellaert, Vivek Kwatra, Sang Min Oh
AI
2005
Springer
13 years 7 months ago
Unifying tree decompositions for reasoning in graphical models
The paper provides a unifying perspective of tree-decomposition algorithms appearing in various automated reasoning areas such as join-tree clustering for constraint-satisfaction ...
Kalev Kask, Rina Dechter, Javier Larrosa, Avi Dech...
ECCV
2000
Springer
14 years 9 months ago
Non-parametric Model for Background Subtraction
Abstract. Background subtraction is a method typically used to segment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the sc...
Ahmed M. Elgammal, David Harwood, Larry S. Davis
CORR
2010
Springer
67views Education» more  CORR 2010»
13 years 7 months ago
Learning Latent Tree Graphical Models
Myung Jin Choi, Vincent Y. F. Tan, Animashree Anan...