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ADVERSARIAL TRAINING OF MACHINE LEARNING MODELS

机译:机器学习模型的对抗训练

摘要

This document relates to training of machine learning models such as neural networks. One example method involves providing a machine learning model having one or more layers and associated parameters and performing a pretraining stage on the parameters of the machine learning model to obtain pretrained parameters. The example method also involves performing a tuning stage on the machine learning model by using labeled training samples to tune the pretrained parameters. The tuning stage can include performing noise adjustment of the labeled training examples to obtain noise-adjusted training samples. The tuning stage can also include adjusting the pretrained parameters based at least on the labeled training examples and the noise-adjusted training examples to obtain adapted parameters. The example method can also include outputting a tuned machine learning model having the adapted parameters.
机译:本文档涉及诸如神经网络等机器学习模型的培训。一个示例方法涉及提供具有一个或多个层和相关参数的机器学习模型,并对机器学习模型的参数执行预先训练阶段以获得预磨平参数。示例方法还涉及通过使用标记的训练样本对机器学习模型执行调谐阶段来调整预磨平的参数。调谐阶段可以包括执行标记的训练示例的噪声调整以获得噪声调整的训练样本。调谐阶段还可以包括至少基于标记的训练示例和噪声调整后的训练示例来调整预制参数,以获得适应的参数。示例方法还可以包括输出具有适应参数的调谐机学习模型。

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