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COLT
2001
Springer
15 years 9 months ago
Robust Learning - Rich and Poor
A class C of recursive functions is called robustly learnable in the sense I (where I is any success criterion of learning) if not only C itself but even all transformed classes Î...
John Case, Sanjay Jain, Frank Stephan, Rolf Wiehag...

Publication
154views
14 years 6 months ago
Preference elicitation and inverse reinforcement learning
We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous w...
Constantin Rothkopf, Christos Dimitrakakis
BMCBI
2005
153views more  BMCBI 2005»
15 years 4 months ago
Learning Statistical Models for Annotating Proteins with Function Information using Biomedical Text
Background: The BioCreative text mining evaluation investigated the application of text mining methods to the task of automatically extracting information from text in biomedical ...
Soumya Ray, Mark Craven
WSDM
2009
ACM
136views Data Mining» more  WSDM 2009»
15 years 11 months ago
Mining common topics from multiple asynchronous text streams
Text streams are becoming more and more ubiquitous, in the forms of news feeds, weblog archives and so on, which result in a large volume of data. An effective way to explore the...
Xiang Wang 0002, Kai Zhang, Xiaoming Jin, Dou Shen
BMCBI
2006
112views more  BMCBI 2006»
15 years 4 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...