Empirical Risk Minimization with Approximations of Probabilistic Grammars

S. B. Cohen, N. A. Smith

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Probabilistic grammars are generative statistical models that are useful for compositional and sequential structures. We present a framework, reminiscent of structural risk minimization, for empirical risk minimization of the parameters of a fixed probabilistic grammar using the log-loss. We derive sample complexity bounds in this framework that apply both to the supervised setting and the unsupervised setting.
Original languageEnglish
Title of host publicationProceedings of NIPS
PublisherNIPS Foundation
Pages1-9
Number of pages9
Publication statusPublished - 2010

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