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AGGRESSIVE DEVELOPMENT WITH COOPERATIVE GENERATORS

机译:与合作发电机共同发展

摘要

Various systems and methods are described herein for improving the aggressive development of machine learning systems. In machine learning, there is always a trade-off between allowing a machine learning system to learn as much as it can from training data and overfitting on the training data. This trade-off is important because overfitting usually causes performance on new data to be worse. However, various systems and methods can be utilized to separate the process of detailed learning and knowledge acquisition and the process of imposing restrictions and smoothing estimates, thereby allowing machine learning systems to aggressively learn from training data, while mitigating the effects of overfitting on the training data.
机译:本文描述了用于改善机器学习系统的积极发展的各种系统和方法。在机器学习中,始终需要在允许机器学习系统从训练数据中学习尽可能多的知识与过度拟合训练数据之间进行权衡。这种权衡很重要,因为过度拟合通常会使新数据的性能变差。但是,可以使用各种系统和方法来分离详细学习和知识获取的过程以及施加限制和平滑估计的过程,从而允许机器学习系统从训练数据中积极学习,同时减轻过度拟合对训练的影响数据。

著录项

  • 公开/公告号WO2019067960A1

    专利类型

  • 公开/公告日2019-04-04

    原文格式PDF

  • 申请/专利权人 D5AI LLC;

    申请/专利号WO2018US53519

  • 发明设计人 BAKER JAMES K.;

    申请日2018-09-28

  • 分类号G06N20;

  • 国家 WO

  • 入库时间 2022-08-21 11:55:22

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