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cs.CL2019★ 13 cited
DeFINE: DEep Factorized INput Token Embeddings for Neural Sequence Modeling
Sachin Mehta, Rik Koncel-Kedziorski, Mohammad Rastegari +1
For sequence models with large vocabularies, a majority of network parameters lie in the input and output layers. In this work, we describe a new method, DeFINE, for learning deep…
cs.CL2018
Pyramidal Recurrent Unit for Language Modeling
Sachin Mehta, Rik Koncel-Kedziorski, Mohammad Rastegari +1
LSTMs are powerful tools for modeling contextual information, as evidenced by their success at the task of language modeling. However, modeling contexts in very high dimensional sp…