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» On learning with dissimilarity functions
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ECML
2004
Springer
15 years 11 months ago
Batch Reinforcement Learning with State Importance
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Lihong Li, Vadim Bulitko, Russell Greiner
155
Voted
STOC
1993
ACM
117views Algorithms» more  STOC 1993»
15 years 10 months ago
Efficient noise-tolerant learning from statistical queries
In this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of Valiant and its variants. In order to identify the cl...
Michael J. Kearns
WWW
2004
ACM
16 years 6 months ago
Newsjunkie: providing personalized newsfeeds via analysis of information novelty
We present a principled methodology for filtering news stories by formal measures of information novelty, and show how the techniques can be used to custom-tailor newsfeeds based ...
Evgeniy Gabrilovich, Susan T. Dumais, Eric Horvitz
159
Voted
MM
2009
ACM
137views Multimedia» more  MM 2009»
16 years 19 days ago
Lightweight web image reranking
Web image search is inspired by text search techniques; it mainly relies on indexing textual data that surround the image file. But retrieval results are often noisy and image pro...
Adrian Popescu, Pierre-Alain Moëllic, Ioannis...
CSB
2003
IEEE
176views Bioinformatics» more  CSB 2003»
15 years 11 months ago
3D Structural Homology Detection via Unassigned Residual Dipolar Couplings
Recognition of a protein’s fold provides valuable information about its function. While many sequence-based homology prediction methods exist, an important challenge remains: tw...
Christopher James Langmead, Bruce Randall Donald