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» Structured metric learning for high dimensional problems
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JAIR
2010
131views more  JAIR 2010»
15 years 11 days ago
Automatic Induction of Bellman-Error Features for Probabilistic Planning
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
Jia-Hong Wu, Robert Givan
BMCBI
2006
134views more  BMCBI 2006»
15 years 2 months ago
Application of machine learning in SNP discovery
Background: Single nucleotide polymorphisms (SNP) constitute more than 90% of the genetic variation, and hence can account for most trait differences among individuals in a given ...
Lakshmi K. Matukumalli, John J. Grefenstette, Davi...
COLT
2010
Springer
14 years 12 months ago
Forest Density Estimation
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
Anupam Gupta, John D. Lafferty, Han Liu, Larry A. ...
AI
2009
Springer
15 years 8 months ago
Opinion Learning without Emotional Words
This paper shows that a detailed, although non-emotional, description of event or an action can be a reliable source for learning opinions. Empirical results show the practical uti...
Marina Sokolova, Guy Lapalme
ACCV
2010
Springer
14 years 9 months ago
Descriptor Learning Based on Fisher Separation Criterion for Texture Classification
Abstract. This paper proposes a novel method to deal with the representation issue in texture classification. A learning framework of image descriptor is designed based on the Fish...
Yimo Guo, Guoying Zhao, Matti Pietikäinen, Zh...