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ICASSP
2009
IEEE
16 years 1 months ago
Maximizing global entropy reduction for active learning in speech recognition
We propose a new active learning algorithm to address the problem of selecting a limited subset of utterances for transcribing from a large amount of unlabeled utterances so that ...
Balakrishnan Varadarajan, Dong Yu, Li Deng, Alex A...
NIPS
2000
15 years 7 months ago
Learning Joint Statistical Models for Audio-Visual Fusion and Segregation
People can understand complex auditory and visual information, often using one to disambiguate the other. Automated analysis, even at a lowlevel, faces severe challenges, includin...
John W. Fisher III, Trevor Darrell, William T. Fre...
JMLR
2006
153views more  JMLR 2006»
15 years 6 months ago
Collaborative Multiagent Reinforcement Learning by Payoff Propagation
In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...
Jelle R. Kok, Nikos A. Vlassis
CORR
2011
Springer
183views Education» more  CORR 2011»
14 years 10 months ago
Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction
For large, real-world inductive learning problems, the number of training examples often must be limited due to the costs associated with procuring, preparing, and storing the tra...
Foster J. Provost, Gary M. Weiss
AMFG
2007
IEEE
283views Biometrics» more  AMFG 2007»
15 years 10 months ago
Learning Personal Specific Facial Dynamics for Face Recognition from Videos
In this paper, we present an effective approach for spatiotemporal face recognition from videos using an Extended set of Volume LBP (Local Binary Pattern features) and a boosting s...
Abdenour Hadid, Matti Pietikäinen, Stan Z. Li