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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
BMCBI
2007
106views more  BMCBI 2007»
13 years 7 months ago
Modeling SAGE tag formation and its effects on data interpretation within a Bayesian framework
Background: Serial Analysis of Gene Expression (SAGE) is a high-throughput method for inferring mRNA expression levels from the experimentally generated sequence based tags. Stand...
Michael A. Gilchrist, Hong Qin, Russell L. Zaretzk...
ACL
2012
11 years 10 months ago
Estimating Compact Yet Rich Tree Insertion Grammars
We present a Bayesian nonparametric model for estimating tree insertion grammars (TIG), building upon recent work in Bayesian inference of tree substitution grammars (TSG) via Dir...
Elif Yamangil, Stuart M. Shieber
NIPS
1998
13 years 8 months ago
Maximum Conditional Likelihood via Bound Maximization and the CEM Algorithm
We present the CEM (Conditional Expectation Maximization) algorithm as an extension of the EM (Expectation Maximization) algorithm to conditional density estimation under missing ...
Tony Jebara, Alex Pentland
AMDO
2010
Springer
13 years 6 months ago
Estimating 3D Pose via Stochastic Search and Expectation Maximization
In this paper an approach is described to estimate 3D pose using a part based stochastic method. A proposed representation of the human body is explored defined over joints that e...
Ben Daubney, Xianghua Xie