Jagadeesh Jagarlamudi, University of Maryland, USA.

The language barrier in many multilingual natural language processing (NLP) tasks, such as name transliteration, mining bilingual word translations, etc., can be overcome by mapping objects (names and words in the respective tasks) from different languages (or "views") into a common low-dimensional subspace. The central idea of our work is to learn low-dimensional subspaces (or interlingual representations) that are effective for various multilingual and monolingual NLP tasks... read more

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