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METHOD AND SYSTEM FOR TRACING A LEARNING SOURCE OF AN EXPLAINABLE ARTIFICIAL INTELLIGENCE MODEL

机译:跟踪可解释的人工智能模型学习源的方法和系统

摘要

This disclosure relates generally to artificial intelligence system, and more particularly to method and system for tracing a learning source of an explainable artificial intelligence (AI) model. In one example, the method may include receiving a desired behavior of the explainable AI model with respect to input data, generating a learning graph based on similarities among a plurality of learning sources with respect to the input data for the desired behavior and for a current behavior, retracing a learning of the explainable AI model by iteratively comparing the learning graph for the desired behavior and for the current behavior at each of a plurality of layers of the explainable AI model starting from an outer layer, and detecting the learning source responsible for the current behavior based on the retracing.
机译:本公开总体上涉及人工智能系统,并且更具体地涉及用于追踪可解释的人工智能(AI)模型的学习源的方法和系统。在一个示例中,该方法可以包括:接收可解释的AI模型相对于输入数据的期望行为;基于多个学习源之间的相似性,相对于针对期望行为和当前的输入数据,生成学习图。行为,通过迭代比较从外层开始的可解释AI模型的多个层中的每一层的期望行为和当前行为的学习图,来追溯可解释AI模型的学习,并检测负责该行为的学习源基于跟踪的当前行为。

著录项

  • 公开/公告号US2019370697A1

    专利类型

  • 公开/公告日2019-12-05

    原文格式PDF

  • 申请/专利权人 WIPRO LIMITED;

    申请/专利号US201816043209

  • 发明设计人 MANJUNATH RAMACHANDRA IYER;

    申请日2018-07-24

  • 分类号G06N99;G06N7;G06K9/62;G06T11/20;

  • 国家 US

  • 入库时间 2022-08-21 11:18:42

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