Grammar Induction for Minimalist Grammars using Variational Bayesian Inference : A Technical Report
Eva Portelance, Amelia Bruno, Daniel Harasim, Leon Bergen, Timothy, J. O'Donnell
TL;DR
This paper introduces a formal probabilistic framework for minimalist grammar induction and presents a variational Bayesian inference algorithm to estimate grammar parameters.
Contribution
It formalizes minimalist grammar within a probabilistic model and develops a variational Bayesian inference method for parameter estimation.
Findings
Successful application of variational Bayesian inference to minimalist grammar formalization
Provides a new algorithm for probabilistic grammar induction
Advances formal understanding of grammar parameter estimation
Abstract
The following technical report presents a formal approach to probabilistic minimalist grammar parameter estimation. We describe a formalization of a minimalist grammar. We then present an algorithm for the application of variational Bayesian inference to this formalization.
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Taxonomy
TopicsNatural Language Processing Techniques · Algorithms and Data Compression · Topic Modeling