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ADJUSTING AUTOMATED NEURAL NETWORK GENERATION BASED ON EVALUATION OF CANDIDATE NEURAL NETWORKS

机译:基于候选神经网络评估的自动神经网络生成调整

摘要

A method includes determining, by a processor of a computing device, an expected performance or reliability of a first neural network of a first plurality of neural networks. The expected performance or reliability is determined based on a vector representing at least a portion of the first neural network, where the first neural network is generated based on an automated generative technique (e.g., a genetic algorithm) and where the first plurality of neural networks corresponds to a first epoch of the automated generative technique. The method also includes responsive to the expected performance or reliability of the first neural network failing to satisfy a threshold, adjusting a parameter of the automated generative technique. The method further includes, during a second epoch of the automated generative technique, generating a second plurality of neural networks based at least in part on the adjusted parameter.
机译:一种方法,包括由计算设备的处理器确定第一多个神经网络中的第一神经网络的预期性能或可靠性。基于代表第一神经网络的至少一部分的向量来确定预期性能或可靠性,其中基于自动生成技术(例如,遗传算法)生成第一神经网络,并且其中第一多个神经网络对应于自动生成技术的第一个时代。该方法还包括响应于第一神经网络的预期性能或可靠性不满足阈值,调整自动生成技术的参数。该方法还包括在自动生成技术的第二时期期间,至少部分地基于调整后的参数来生成第二多个神经网络。

著录项

  • 公开/公告号US2019122119A1

    专利类型

  • 公开/公告日2019-04-25

    原文格式PDF

  • 申请/专利权人 SPARKCOGNITION INC.;

    申请/专利号US201715793890

  • 发明设计人 SYED MOHAMMAD AMIR HUSAIN;

    申请日2017-10-25

  • 分类号G06N3/08;G06N3/04;

  • 国家 US

  • 入库时间 2022-08-21 12:07:26

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