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» On learning with dissimilarity functions
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JMLR
2010
82views more  JMLR 2010»
13 years 4 months ago
Negative Results for Active Learning with Convex Losses
We study the problem of active learning with convex loss functions. We prove that even under bounded noise constraints, the minimax rates for proper active learning are often no b...
Steve Hanneke, Liu Yang
BMCBI
2007
120views more  BMCBI 2007»
13 years 9 months ago
Quantitative sequence-function relationships in proteins based on gene ontology
Background: The relationship between divergence of amino-acid sequence and divergence of function among homologous proteins is complex. The assumption that homologs share function...
Vineet Sangar, Daniel J. Blankenberg, Naomi Altman...
ICML
2008
IEEE
14 years 10 months ago
A worst-case comparison between temporal difference and residual gradient with linear function approximation
Residual gradient (RG) was proposed as an alternative to TD(0) for policy evaluation when function approximation is used, but there exists little formal analysis comparing them ex...
Lihong Li
SIGGRAPH
2010
ACM
14 years 1 months ago
Learning behavior styles with inverse reinforcement learning
We present a method for inferring the behavior styles of character controllers from a small set of examples. We show that a rich set of behavior variations can be captured by dete...
Seong Jae Lee, Zoran Popovic
CICLING
2009
Springer
14 years 10 months ago
Semantic Clustering for a Functional Text Classification Task
Abstract. We describe a semantic clustering method designed to address shortcomings in the common bag-of-words document representation for functional semantic classification tasks....
Thomas Lippincott, Rebecca J. Passonneau