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IJON
1998
158views more  IJON 1998»
13 years 7 months ago
Bayesian Kullback Ying-Yang dependence reduction theory
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...
Lei Xu
KDD
2008
ACM
186views Data Mining» more  KDD 2008»
14 years 7 months ago
Cut-and-stitch: efficient parallel learning of linear dynamical systems on smps
Multi-core processors with ever increasing number of cores per chip are becoming prevalent in modern parallel computing. Our goal is to make use of the multi-core as well as multi...
Lei Li, Wenjie Fu, Fan Guo, Todd C. Mowry, Christo...
JMLR
2011
148views more  JMLR 2011»
13 years 2 months ago
Bayesian Generalized Kernel Mixed Models
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
Zhihua Zhang, Guang Dai, Michael I. Jordan
BMCBI
2006
112views more  BMCBI 2006»
13 years 7 months ago
A correlated motif approach for finding short linear motifs from protein interaction networks
Background: An important class of interaction switches for biological circuits and disease pathways are short binding motifs. However, the biological experiments to find these bin...
Soon-Heng Tan, Hugo Willy, Wing-Kin Sung, See-Kion...
UAI
2001
13 years 8 months ago
Exact Inference in Networks with Discrete Children of Continuous Parents
Many real life domains contain a mixture of discrete and continuous variables and can be modeled as hybrid Bayesian Networks (BNs). An important subclass of hybrid BNs are conditi...
Uri Lerner, Eran Segal, Daphne Koller