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arXiv · 1803.02839

The emergent algebraic structure of RNNs and embeddings in NLP

Sean A. Cantrell
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Abstract

We examine the algebraic and geometric properties of a uni-directional GRU and word embeddings trained end-to-end on a text classification task. A hyperparameter search over word embedding dimension, GRU hidden dimension, and a linear combination of the GRU outputs is performed. We conclude that words naturally embed themselves in a Lie group and that RNNs form a nonlinear representation of the group. Appealing to these results, we propose a novel class of recurrent-like neural networks and a word embedding scheme.

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Sean A. Cantrell. 2018-03-07. The emergent algebraic structure of RNNs and embeddings in NLP. https://arxiv.org/abs/1803.02839

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