【推荐】RNN最新研究进展综述

                                                                                                                                                                                      

点击上方 “机器学习研究会”可以订阅

摘要

 

转自：爱可可-爱生活

论文《Recent Advances in Recurrent Neural Networks》摘要：

Recurrent neural networks (RNNs) are capable of learning features and long term dependencies from sequential and time-series data. The RNNs have a stack of non-linear units where at least one connection between units forms a directed cycle. A well-trained RNN can model any dynamical system; however, training RNNs is mostly plagued by issues in learning long-term dependencies. In this paper, we present a survey on RNNs and several new advances for newcomers and professionals in the field. The fundamentals and recent advances are explained and the research challenges are introduced.

链接：

https://arxiv.org/abs/1801.01078

• 
  

原文链接：

https://m.weibo.cn/1402400261/4192691216378025

“完整内容”请点击【阅读原文】

↓↓↓