%0 Conference Proceedings
%T Training Structured Prediction Energy Networks with Indirect Supervision
%A Rooshenas, Amirmohammad
%A Kamath, Aishwarya
%A McCallum, Andrew
%Y Walker, Marilyn
%Y Ji, Heng
%Y Stent, Amanda
%S Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F rooshenas-etal-2018-training
%X This paper introduces rank-based training of structured prediction energy networks (SPENs). Our method samples from output structures using gradient descent and minimizes the ranking violation of the sampled structures with respect to a scalar scoring function defined with domain knowledge. We have successfully trained SPEN for citation field extraction without any labeled data instances, where the only source of supervision is a simple human-written scoring function. Such scoring functions are often easy to provide; the SPEN then furnishes an efficient structured prediction inference procedure.
%R 10.18653/v1/N18-2021
%U https://aclanthology.org/N18-2021
%U https://doi.org/10.18653/v1/N18-2021
%P 130-135