Abstract. The present paper presents a new approach of how to convert Gold-style [4] learning in the limit into stochastically finite learning with high confidence. We illustrate t...
Abstract. Stochastic deterministic finite automata have been introduced and are used in a variety of settings. We report here a number of results concerning the learnability of th...
We present in this paper a new learning problem called learning distributions from experts. In the case we study the experts are stochastic deterministic finite automata (sdfa). W...
Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to potential ap...
Abstract. Stochastic deterministic finite automata have been introduced and are used in a variety of settings. We use them to model musical styles: a same automaton can be used to...