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TRAINING MACHINE LEARNING MODELS ON MULTIPLE MACHINE LEARNING TASKS

机译:多个机器学习任务上的训练机器学习模型

摘要

A method of training a machine learning model having multiple parameters, in which the machine learning model has been trained on a first machine learning task to determine first values of the parameters of the machine learning model. The method includes determining, for each of the parameters, a respective measure of an importance of the parameter to the machine learning model achieving acceptable performance on the first machine learning task; obtaining training data for training the machine learning model on a second, different machine learning task; and training the machine learning model on the second machine learning task by training the machine learning model on the training data to adjust the first values of the parameters so that the machine learning model achieves an acceptable level of performance on the second machine learning task while maintaining an acceptable level of performance on the
机译:一种训练具有多个参数的机器学习模型的方法,其中已经在第一机器学习任务上训练了机器学习模型以确定机器学习模型的参数的第一值。该方法包括:对于每个参数,确定参数对机器学习模型的重要性的相应度量,以在第一机器学习任务上实现可接受的性能;获取用于在第二个不同的机器学习任务上训练机器学习模型的训练数据;通过在训练数据上训练机器学习模型以调整参数的第一值来训练第二机器学习任务上的机器学习模型,以便机器学习模型在维持第二机器学习任务的同时达到可接受的性能水平可接受的性能水平

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