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AUTOMATED FINE-TUNING OF A PRE-TRAINED NEURAL NETWORK FOR TRANSFER LEARNING

机译:预先训练的神经网络自动调整转移学习

摘要

In an embodiment, a method for fine-tuning a pre-trained neural network for transfer learning, the method comprising obtaining a first target feature vector from a first layer of a pre-trained neural network responsive to a first target data element of a target dataset passing therethrough, obtaining a first source feature vector associated with the first layer of the pre-trained neural network, calculating a first divergence value for the first layer of the pre-trained neural network based at least in part on the first target feature vector and the first source feature vector, and setting a learning rate for the first layer of the pre-trained neural network based at least in part on the first divergence value.
机译:在一个实施例中,用于微调预先训练的神经网络的方法用于传输学习,该方法包括响应于目标的第一目标数据元素从预先训练的神经网络的第一层获得第一目标特征向量通过其传递的数据集,获得与预训练神经网络的第一层相关联的第一源特征向量,至少部分地基于第一目标特征向量来计算预先训练的神经网络的第一层的第一发散值和第一源特征向量,并至少部分地基于第一发散值来为第一训练神经网络的第一层的学习率。

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