NeurIPS 2020poster34 citations
Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration
Hanjun Dai, Rishabh Singh, Bo Dai, Charles A. Sutton, Dale Schuurmans
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.
BibTeX
@inproceedings{NEURIPS2020_7612936d,
author = {Dai, Hanjun and Singh, Rishabh and Dai, Bo and Sutton, Charles and Schuurmans, Dale},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin},
pages = {10443--10455},
publisher = {Curran Associates, Inc.},
title = {Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration},
url = {https://proceedings.neurips.cc/paper_files/paper/2020/file/7612936dcc85282c6fa4dd9d4ffe57f1-Paper.pdf},
volume = {33},
year = {2020}
}