Deep Frank-Wolfe for neural network optimization

Learning a deep neural network requires solving a challenging optimization problem: it is a high-dimensional, non-convex and non-smooth minimization problem with a large number of terms. The current practice in neural network optimization is to rely on the stochastic gradient descent (SGD) algorithm...

詳細記述

書誌詳細
主要な著者: Berrada, L, Zisserman, A, Kumar, MP
フォーマット: Internet publication
言語:English
出版事項: arXiv 2018

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