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UAI
2003
13 years 6 months ago
Learning Module Networks
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
CVPR
2010
IEEE
13 years 11 months ago
Weakly-Supervised Hashing in Kernel Space
The explosive growth of the vision data motivates the recent studies on efficient data indexing methods such as locality-sensitive hashing (LSH). Most existing approaches perform...
Yadong Mu, Jialie Shen, Shuicheng Yan
BMCBI
2008
125views more  BMCBI 2008»
13 years 5 months ago
MAID : An effect size based model for microarray data integration across laboratories and platforms
Background: Gene expression profiling has the potential to unravel molecular mechanisms behind gene regulation and identify gene targets for therapeutic interventions. As microarr...
Ivan Borozan, Limin Chen, Bryan Paeper, Jenny E. H...
CSDA
2006
90views more  CSDA 2006»
13 years 5 months ago
Estimation in covariate-adjusted regression
Abstract: The method of covariate adjusted regression was recently proposed for situations where both predictors and response in a regression model are not directly observed, but a...
Damla Sentürk, Danh V. Nguyen
MM
2004
ACM
167views Multimedia» more  MM 2004»
13 years 10 months ago
Learning an image manifold for retrieval
We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
Xiaofei He, Wei-Ying Ma, HongJiang Zhang