Empirical Risk Minimization with Approximations of Probabilistic Grammars

S. B. Cohen, N. A. Smith

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


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
Number of pages9
Publication statusPublished - 2010

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