Dec 18, 2017 · In this paper we propose a simple technique called fraternal dropout that takes advantage of dropout to achieve this goal. Specifically, we ...
Oct 31, 2017 · In this paper we propose a simple technique called fraternal dropout that takes advantage of dropout to achieve this goal. Specifically, we ...
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In this paper we propose a simple regularization based on dropout that we call fraternal dropout, where we minimize an equally weighted sum of prediction losses ...
Mar 28, 2018 · In this paper we propose a simple technique called fraternal dropout that takes advantage of dropout to achieve this goal. Specifically, we ...
A simple technique called fraternal dropout is proposed that takes advantage of dropout to train two identical copies of an RNN (that share parameters) with ...
Oct 30, 2017 · Fraternal Dropout is a regularization method for recurrent neural networks that trains two identical copies of an RNN (that share parameters) with different ...
This repository contains the code originally forked from the AWD-LSTM Language Model that is simplified and modified to present the performance of Fraternal ...
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Fraternal Dropout is a regularization method that addresses this problem by training two identical copies of an RNN with different dropout masks while ...
Nov 7, 2017 · We had to alter activation + temporal activation regularization (AR/TAR) which collides with fraternal dropout (see the paper for details).