2017 ASimpleRegularizationbasedAlgor

• (Yang, Lu & Zheng, 2017) ⇒ Wei Yang, Wei Lu, and Vincent Zheng. (2017). “A Simple Regularization-based Algorithm for Learning Cross-Domain Word Embeddings.” In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing.

Subject Headings: Domain-Specific Word Embeddings, Transfer Learning.

Notes

• copy of the presentation slides: https://docs.google.com/presentation/d/190KPs27ijX-ybxAnTVj9KWpTIb14fSvdztkIHAHPcf0/

Cited By

• http://scholar.google.com/scholar?q=%222017%22+A+Simple+Regularization-based+Algorithm+for+Learning+Cross-Domain+Word+Embeddings

Quotes

Abstract

Learning word embeddings has received a significant amount of attention recently. Often, word embeddings are learned in an unsupervised manner from a large collection of text. The genre of the text typically plays an important role in the effectiveness of the resulting embeddings. How to effectively train word embedding models using data from different domains remains a problem that is underexplored. In this paper, we present a simple yet effective method for learning word embeddings based on text from different domains. We demonstrate the effectiveness of our approach through extensive experiments on various downstream NLP tasks.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2017 ASimpleRegularizationbasedAlgor	Wei Lu Wei Yang Vincent Zheng			A Simple Regularization-based Algorithm for Learning Cross-Domain Word Embeddings