Latest RNN Techniques: Attention-Augmented RNN and Four Models

Latest RNN Techniques: Attention-Augmented RNN and Four Models

1 New Intelligence Compilation Source: distill.pub/2016/augmented-rnns Authors: Chris Olah & Shan Carter, Google Brain Translator: Wen Fei Today is September 10, 2016 Countdown to AI WORLD 2016 World Artificial Intelligence Conference: 38 days Countdown for Early Bird Tickets: 9 days [New Intelligence Guide] The Google Brain team, led by Chris Olah & Shan Carter, has … Read more

Overview of Dropout Application in RNNs

Overview of Dropout Application in RNNs

[Introduction] This article provides the background and overview of Dropout, as well as a parameter analysis of its application in language modeling using LSTM/GRU recurrent neural networks. Author|Adrian G Compiled by|Zhuanzhi Organized by|Yingying Dropout Inspired by the role of gender in evolution, Hinton et al. first proposed Dropout, which temporarily removes units from the neural … Read more

Solving the Vanishing Gradient Problem in RNNs

Solving the Vanishing Gradient Problem in RNNs

Click the above “MLNLP” to select the “star” public account Essential content delivered promptly Author: Yulin Ling CS224N(1.29)Vanishing Gradients, Fancy RNNs Vanishing Gradient The figure below is a more vivid example. Suppose we need to predict the next word after the sentence “The writer of the books”. Due to the vanishing gradient, the influence of … Read more