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LEARNING NON-DIFFERENTIABLE WEIGHTS OF NEURAL NETWORKS USING EVOLUTIONARY STRATEGIES

机译:运用进化策略学习神经网络的不可分权重

摘要

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network. The neural network has a plurality of differentiable weights and a plurality of non-differentiable weights. One of the methods includes determining trained values of the plurality of differentiable weights and the non-differentiable weights by repeatedly performing operations that include determining an update to the current values of the plurality of differentiable weights using a machine learning gradient-based training technique and determining, using an evolution strategies (ES) technique, an update to the current values of a plurality of distribution parameters.
机译:用于训练神经网络的方法,系统和装置,包括在计算机存储介质上编码的计算机程序。该神经网络具有多个可微分的权重和多个不可微分的权重。方法之一包括通过重复执行包括使用基于机器学习的梯度的训练技术来确定对多个可微分权重的当前值的更新的操作来确定多个可微分权重和不可微分的权重的训练值,以及确定使用进化策略(ES)技术,更新多个分布参数的当前值。

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