首页> 外国专利> MANAGEMENT AND EVALUATION OF MACHINE-LEARNED MODELS BASED ON LOCALLY LOGGED DATA

MANAGEMENT AND EVALUATION OF MACHINE-LEARNED MODELS BASED ON LOCALLY LOGGED DATA

机译:基于本地记录数据的机器学习模型的管理与评估

摘要

The present disclosure provides systems and methods for the management and/or evaluation of machine-learned models based on locally logged data. In one example, a user computing device can obtain a machine-learned model (e.g., from a server computing device) and can evaluate at least one performance metric for the machine-learned model. In particular, the at least one performance metric for the machine-learned model can be evaluated relative to data that is stored locally at the user computing device. The user computing device and/or the server computing device can determine whether to activate the machine-learned model on the user computing device based at least in part on the at least one performance metric. In another example, the user computing device can evaluate a plurality of machine-learned models against locally stored data. At least one of the models can be selected based on the evaluated performance metrics.
机译:本公开提供了用于基于本地记录数据的机器学习模型的管理和/或评估的系统和方法。 在一个示例中,用户计算设备可以获得机器学习模型(例如,从服务器计算设备),并且可以评估机器学习模型的至少一个性能度量。 具体地,可以相对于在用户计算设备处本地存储的数据来评估机器学习模型的至少一个性能度量。 用户计算设备和/或服务器计算设备可以至少部分地基于至少一个性能度量来确定是否基于用户计算设备上激活机器学习模型。 在另一示例中,用户计算设备可以针对本地存储的数据评估多个机器学习模型。 可以基于评估的性能度量来选择至少一个模型。

著录项

  • 公开/公告号EP3542322B1

    专利类型

  • 公开/公告日2021-11-03

    原文格式PDF

  • 申请/专利权人

    申请/专利号EP20170784092

  • 发明设计人 BONAWITZ KEITH;RAMAGE DANIEL;

    申请日2017-09-25

  • 分类号G06N20;

  • 国家 EP

  • 入库时间 2022-08-24 22:04:02

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