Training Structured Prediction Energy Networks with Indirect Supervision

ACL 2018

Training Structured Prediction Energy Networks with Indirect Supervision

Jun 22, 2018
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Abstract: 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. Authors: Amirmohammad Rooshenas, Aishwarya Kamath, Andrew McCallum (University of Massachusetts Amherst)

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