In this paper, we propose a new framework for the computational learning of formal grammars with positive data. In this model, both syntactic and semantic information are taken int...
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...
This paper describes a new sampling-based heuristic for tree search named SAGE and presents an analysis of its performance on the problem of grammar induction. This last work has b...
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...