2015 DeepUnorderedCompositionRivalsS

• (Iyyer et al., 2015) ⇒ Mohit Iyyer, Varun Manjunatha, Jordan Boyd-Graber, and Hal Daumé III. (2015). “Deep Unordered Composition Rivals Syntactic Methods for Text Classification.” In: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2015]).

Subject Headings:

Notes

• Presentation https://www.youtube.com/watch?v=y1_0i1RF74c

Cited By

• http://scholar.google.com/scholar?q=%222015%22+Deep+Unordered+Composition+Rivals+Syntactic+Methods+for+Text+Classification

Quotes

Abstract

Many existing deep learning models for natural language processing tasks focus on learning the compositionality of their inputs, which requires many expensive computations. We present a simple deep neural network that competes with and, in some cases, outperforms such models on sentiment analysis and factoid question answering tasks while taking only a fraction of the training time. While our model is syntactically-ignorant, we show significant improvements over previous bag-of-words models by deepening our network and applying a novel variant of dropout. Moreover, our model performs better than syntactic models on datasets with high syntactic variance. We show that our model makes similar errors to syntactically-aware models, indicating that for the tasks we consider, nonlinearly transforming the input is more important than tailoring a network to incorporate word order and syntax.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2015 DeepUnorderedCompositionRivalsS	Mohit Iyyer Hal Daumé, III Varun Manjunatha Jordan Boyd-Graber			Deep Unordered Composition Rivals Syntactic Methods for Text Classification						2015