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» Topologically-constrained latent variable models
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105
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BMCBI
2006
104views more  BMCBI 2006»
15 years 15 days ago
Semi-supervised discovery of differential genes
Background: Various statistical scores have been proposed for evaluating the significance of genes that may exhibit differential expression between two or more controlled conditio...
Shigeyuki Oba, Shin Ishii
90
Voted
NIPS
2007
15 years 1 months ago
Expectation Maximization and Posterior Constraints
The expectation maximization (EM) algorithm is a widely used maximum likelihood estimation procedure for statistical models when the values of some of the variables in the model a...
João Graça, Kuzman Ganchev, Ben Task...
98
Voted
PAMI
2008
182views more  PAMI 2008»
15 years 11 days ago
Gaussian Process Dynamical Models for Human Motion
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
Jack M. Wang, David J. Fleet, Aaron Hertzmann
89
Voted
PVLDB
2010
119views more  PVLDB 2010»
14 years 11 months ago
An Architecture for Parallel Topic Models
This paper describes a high performance sampling architecture for inference of latent topic models on a cluster of workstations. Our system is faster than previous work by over an...
Alexander J. Smola, Shravan Narayanamurthy
ICPR
2008
IEEE
15 years 6 months ago
Tracking human body by using particle filter Gaussian process Markov-switching model
The goal of this article is to present an effective and robust tracking algorithm for nonlinear feet motion by deploying particle filter integrated with Gaussian process latent v...
Jing Wang, Hong Man, Yafeng Yin