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...
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...
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...
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...
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...