Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration

Abstract

Discrete structures play an important role in applications like program language modeling and software engineering. Current approaches to predicting complex structures typically consider autoregressive models for their tractability, with some sacrifice in flexibility.