Sparse coding is a new field in signal processing with possible applications to source coding. In this paper we present a new method that combines the problems of sparse signal a...
Mehrdad Yaghoobi, Thomas Blumensath, Mike E. Davie...
Logics for knowledge representation suffer from overspecialization: while each logic may provide an ideal representation formalism for some problems, it is less than optimal for o...
Grigoris Antoniou, David Billington, Guido Governa...
Expressive knowledge representations with flexible semantic similarity measures are central for the functioning of semantic information retrieval, information integration, matchmak...
To classify a large number of unlabeled examples we combine a limited number of labeled examples with a Markov random walk representation over the unlabeled examples. The random w...
Constructive induction divides the problem of learning an inductive hypothesis into two intertwined searches: one—for the “best” representation space, and two—for the “be...