Stuart Russell


2017

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Adversarial Training for Relation Extraction
Yi Wu | David Bamman | Stuart Russell
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

Adversarial training is a mean of regularizing classification algorithms by generating adversarial noise to the training data. We apply adversarial training in relation extraction within the multi-instance multi-label learning framework. We evaluate various neural network architectures on two different datasets. Experimental results demonstrate that adversarial training is generally effective for both CNN and RNN models and significantly improves the precision of predicted relations.

2016

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The Physics of Text: Ontological Realism in Information Extraction
Stuart Russell | Ole Torp Lassen | Justin Uang | Wei Wang
Proceedings of the 5th Workshop on Automated Knowledge Base Construction