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ICML
2008
IEEE
14 years 8 months ago
Apprenticeship learning using linear programming
In apprenticeship learning, the goal is to learn a policy in a Markov decision process that is at least as good as a policy demonstrated by an expert. The difficulty arises in tha...
Umar Syed, Michael H. Bowling, Robert E. Schapire
WWW
2004
ACM
14 years 8 months ago
Dealing with different distributions in learning from
In the problem of learning with positive and unlabeled examples, existing research all assumes that positive examples P and the hidden positive examples in the unlabeled set U are...
Xiaoli Li, Bing Liu
CVPR
2010
IEEE
14 years 3 months ago
Piecewise Planar and Non-Planar Stereo for Urban Scene Reconstruction
Piecewise planar models for stereo have recently become popular for modeling indoor and urban outdoor scenes. The strong planarity assumption overcomes the challenges presented by...
David Gallup, Jan-Michael Frahm, Marc Pollefeys
AAAI
1993
13 years 9 months ago
Learning Semantic Grammars with Constructive Inductive Logic Programming
Automating the construction of semantic grammars is a di cult and interesting problem for machine learning. This paper shows how the semantic-grammar acquisition problem can be vi...
John M. Zelle, Raymond J. Mooney
FOSSACS
2008
Springer
13 years 9 months ago
Compositional Methods for Information-Hiding
Protocols for information-hiding often use randomized primitives to obfuscate the link between the observables and the information to be protected. The degree of protection provide...
Christelle Braun, Konstantinos Chatzikokolakis, Ca...