We present an algorithm, called the offset tree, for learning in situations where a loss associated with different decisions is not known, but was randomly probed. The algorithm i...
We introduce the notion of a multiprofile and use it for finding subtle motifs in DNA sequences. Multiprofiles generalize the notion of a profile and allow one to detect subtle co...
We continue the study of the linear complexity of binary sequences, independently introduced by Sidel'nikov and Lempel, Cohn, and Eastman. These investigations were originated...
We introduce the problem of grammar mining, where patterns are context-free grammars, as a generalization of a large number of common pattern mining tasks, such as tree, sequence ...
Abstract. We consider an upper confidence bound algorithm for Markov decision processes (MDPs) with deterministic transitions. For this algorithm we derive upper bounds on the onl...