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BMCBI
2004
229views more  BMCBI 2004»
13 years 10 months ago
Automatic annotation of protein motif function with Gene Ontology terms
Background: Conserved protein sequence motifs are short stretches of amino acid sequence patterns that potentially encode the function of proteins. Several sequence pattern search...
Xinghua Lu, Chengxiang Zhai, Vanathi Gopalakrishna...
BMCBI
2007
129views more  BMCBI 2007»
13 years 10 months ago
Exploring inconsistencies in genome-wide protein function annotations: a machine learning approach
Background: Incorrectly annotated sequence data are becoming more commonplace as databases increasingly rely on automated techniques for annotation. Hence, there is an urgent need...
Carson M. Andorf, Drena Dobbs, Vasant Honavar
COLT
2008
Springer
13 years 11 months ago
The True Sample Complexity of Active Learning
We describe and explore a new perspective on the sample complexity of active learning. In many situations where it was generally believed that active learning does not help, we sh...
Maria-Florina Balcan, Steve Hanneke, Jennifer Wort...
ICMLA
2010
13 years 8 months ago
Multi-Agent Inverse Reinforcement Learning
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...
Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah,...
ALT
2006
Springer
14 years 7 months ago
The Complexity of Learning SUBSEQ (A)
Higman showed that if A is any language then SUBSEQ(A) is regular, where SUBSEQ(A) is the language of all subsequences of strings in A. We consider the following inductive inferenc...
Stephen A. Fenner, William I. Gasarch