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NIPS
2008
13 years 9 months ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Shenghuo Zhu, Kai Yu, Yihong Gong
ECCV
2008
Springer
14 years 9 months ago
Constrained Maximum Likelihood Learning of Bayesian Networks for Facial Action Recognition
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...
Cassio Polpo de Campos, Yan Tong, Qiang Ji
CVIU
2007
193views more  CVIU 2007»
13 years 7 months ago
Interpretation of complex scenes using dynamic tree-structure Bayesian networks
This paper addresses the problem of object detection and recognition in complex scenes, where objects are partially occluded. The approach presented herein is based on the hypothe...
Sinisa Todorovic, Michael C. Nechyba
BMCBI
2006
117views more  BMCBI 2006»
13 years 7 months ago
The Cluster Variation Method for Efficient Linkage Analysis on Extended Pedigrees
Background: Computing exact multipoint LOD scores for extended pedigrees rapidly becomes infeasible as the number of markers and untyped individuals increase. When markers are exc...
Cornelis A. Albers, Martijn A. R. Leisink, Hilbert...
BMCBI
2008
159views more  BMCBI 2008»
13 years 7 months ago
Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments
Background: Identification of differentially expressed genes is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increas...
Hongya Zhao, Kwok-Leung Chan, Lee-Ming Cheng, Hong...