Vector Space Word Representations (Rani Nelken)
Tuesday, Nov 4 7:30p
Hack/Reduce
Cambridge,
MA
Format
We will end with a quick food and networking session, after our second talk of the evening.
Talk Abstract
NLP has traditionally mapped words to discrete elements without underlying structure. Recent research replaces these models with vector-based representations, efficiently learned using neural networks. The resulting embeddings not only improve performance on a variety of tasks, but also show surprising algebraic structure. I will give a gentle introduction to these exciting developments.
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