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ARTIFICIAL NEURAL NETWORK AND METHOD OF TRAINING AN ARTIFICIAL NEURAL NETWORK WITH EPIGENETIC NEUROGENESIS

机译:人工神经网络和利用表皮神经发生训练人工神经网络的方法

摘要

A method for retraining an artificial neural network trained on data from an old task includes training the artificial neural network on data from a new task different than the old task, calculating a drift, utilizing Sliced Wasserstein Distance, in activation distributions of a series of hidden layer nodes during the training of the artificial neural network with the new task, calculating a number of additional nodes to add to at least one hidden layer based on the drift in the activation distributions, resetting connection weights between input layer nodes, hidden layer nodes, and output layer nodes to values before the training of the artificial neural network on the data from the new task, adding the additional nodes to the at least one hidden layer, and training the artificial neural network on data from the new task.
机译:一种用于对来自旧任务的数据进行训练的人工神经网络进行再训练的方法,包括对来自不同于旧任务的新任务的数据进行人工神经网络的训练,利用切片Wasserstein距离在一系列隐藏的激活分布中计算漂移。层节点在使用新任务进行人工神经网络训练期间,根据激活分布中的漂移计算一些附加节点,以添加到至少一个隐藏层,重置输入层节点,隐藏层节点之间的连接权重,在对来自新任务的数据进行人工神经网络训练之前,将输出层节点的值设置为值,将附加节点添加到至少一个隐藏层,并针对来自新任务的数据对人工神经网络进行训练。

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