English

Improving Minimal Gated Unit for Sequential Data

Machine Learning 2019-06-04 v1 Neural and Evolutionary Computing

Abstract

In order to obtain a model which can process sequential data related to machine translation and speech recognition faster and more accurately, we propose adopting Chrono Initializer as the initialization method of Minimal Gated Unit. We evaluated the method with two tasks: adding task and copy task. As a result of the experiment, the effectiveness of the proposed method was confirmed.

Cite

@article{arxiv.1906.00748,
  title  = {Improving Minimal Gated Unit for Sequential Data},
  author = {Kazuki Takamura and Satoshi Yamane},
  journal= {arXiv preprint arXiv:1906.00748},
  year   = {2019}
}

Comments

2 pages, 5 figures

R2 v1 2026-06-23T09:38:46.759Z