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Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Posted 2024-09-27Updated 2026-03-08Reviewa minute read (About 112 words)   visits

Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Background: RNN

首先介绍了RNN通过hidden state来实现记忆力功能

但指出RNN的训练有梯度消失/爆炸的现象,且记忆会沿序列长度的增加而指数下降,缺乏长期记忆能力。 解决梯度消失/爆炸目前有梯度裁剪和二阶梯度的方法,但成效并不显著

Gated RNN

[[On the Properties of Neural Machine Translation= Encoder–Decoder Approaches]]

Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

http://chen-yulin.github.io/2024/09/27/[OBS]Deep Learning-RNN-Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling/

Author

Chen Yulin

Posted on

2024-09-27

Updated on

2026-03-08

Licensed under

#Research-paperNNNLPRNNGated-NN
On the Properties of Neural Machine Translation= Encoder–Decoder Approaches
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Chen Yulin

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