Learning structured models for string and tree structured data
Amaury Habrard
(2010) Other thesis, Aix-Marseille University (Université de Provence).

Abstract

In this habilitation thesis, we review some approaches for learning structured models for string or structured data. We consider three particular subjects. In a first part, we address the problem of learning stochastic models represented by weighted automata. In a second part, we present two methods based on an oracle. One for learning rational functions over trees, the other for learning a powerful subclass of context-free grammars. Finally, we present some algorithms for learning similarities based on edit distance for string and trees.

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