Learning translations via matrix completion

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Abstract

Bilingual Lexicon Induction is the task of learning word translations without bilingual parallel corpora. We model this task as a matrix completion problem, and present an effective and extendable framework for completing the matrix. This method harnesses diverse bilingual and monolingual signals, each of which may be incomplete or noisy. Our model achieves state-of-the-art performance for both high and low resource languages.

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APA

Wijaya, D., Callahan, B., Hewitt, J., Gao, J., Ling, X., Apidianaki, M., & Callison-Burch, C. (2017). Learning translations via matrix completion. In EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings (pp. 1452–1463). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/d17-1152

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