PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

PAC-learning unambiguous NTS languages
Alexander Clark
In: International Collquium on Grammatical Inference, 20 -22 September 2006, Tokyo, Japan.

Abstract

Non-terminally separated (NTS) languages are a subclass of deterministic context free languages where there is a stable relationship between the substrings of the language and the non-terminals of the grammar. We show that when the distribution of samples is generated by a PCFG, based on the same grammar as the target language, the class of unambiguous NTS languages is PAC-learnable from positive data alone, with polynomial bounds on data and computation.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
Theory & Algorithms
ID Code:2168
Deposited By:Alexander Clark
Deposited On:10 August 2006