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Multi-task neural networks with task-specific paths

机译:具有特定任务路径的多任务神经网络

摘要

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using multi-task neural networks. One of the methods includes receiving a first network input and data identifying a first machine learning task to be performed on the first network input; selecting a path through the plurality of layers in a super neural network that is specific to the first machine learning task, the path specifying, for each of the layers, a proper subset of the modular neural networks in the layer that are designated as active when performing the first machine learning task; and causing the super neural network to process the first network input using (i) for each layer, the modular neural networks in the layer that are designated as active by the selected path and (ii) the set of one or more output layers corresponding to the identified first machine learning task.
机译:用于使用多任务神经网络的方法,系统和装置,包括在计算机存储介质上编码的计算机程序。该方法中的一种包括:接收第一网络输入和标识将在第一网络输入上执行的第一机器学习任务的数据;以及在超级神经网络中选择特定于第一个机器学习任务的穿过多层的路径,该路径为每个层指定该层中模块化神经网络的适当子集,该子集在以下情况下被指定为活动的执行第一项机器学习任务;使超级神经网络使用以下方法处理第一网络输入:(i)每层,该层中的模块化神经网络被选定的路径指定为活动的,以及(ii)对应于一个或多个输出层的一组确定的第一个机器学习任务。

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