Linear algebraic structure of word senses with applications to polysemy

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Linear Algebraic Structure of Word Senses, with Applications to Polysemy Sanjeev Arora Yuanzhi Li Yingyu Liang Tengyu Ma Andrej Risteski Abstract Word embeddings are ubiquitous in NLP and information retrieval, but it’s unclear what they repre-sent when the word is polysemous, i.e., has multiple senses. Here it is shown that multiple word …

Title: Linear Algebraic Structure of Word Senses, with Applications to Polysemy: Authors: Arora, Sanjeev; Li, Yuanzhi; Liang, Yingyu; Ma, Tengyu; Risteski, Andrej

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Title: Linear Algebraic Structure of Word Senses, with Applications to Polysemy Authors: Sanjeev Arora, Yuanzhi Li, Yingyu Liang, Tengyu Ma, Andrej Risteski.

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Word embeddings, neural networks, representation learning . RAND-WALK: a latent variable model approach to word embeddings. With Sanjeev Arora, Yuanzhi Li, Yingyu Liang and Tengyu Ma. Transactions of the Association for Computational Linguistics (TACL), Vol 4, 2016 ; Linear algebraic structure of word senses, with applications to …

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Linear Algebraic Structure of Word Senses, with Applications to Polysemy arXiv:1601.03764v1 [cs.CL] 14 Jan 2016 Sanjeev Arora Yuanzhi Li …

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[1601.03764] Linear Algebraic Structure of Word Senses

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