Empirical Risk Minimization with Approximations of Probabilistic Grammars

2010-12-01T00:00:00Z (GMT) by Shay B. Cohen Noah A. Smith

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.