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    • 86. 发明申请
    • INTERACTIVE LEARNING
    • 互动学习
    • US20160117603A1
    • 2016-04-28
    • US14748375
    • 2015-06-24
    • INTERNATIONAL BUSINESS MACHINES CORPORATION
    • Brian P. GaucherJonathan LenchnerDavid O. MelvilleValentina Salapura
    • G06N99/00G06N7/00
    • G06N99/005
    • A system and method are provided for shared machine learning. The method includes providing a model to a plurality of agents included in a machine learning system. The model specifies attributes and attribute value data types for an event in which the agents act. The method further includes receiving agent-provided inputs during an instance of the event. The agent-provided inputs include estimated attribute values that are consistent with the attribute value data types. The method also includes determining expertise weights for at least some agents in response to at least one ground-truth which is learned from the estimated attribute values. The method additionally includes determining an estimate value for one or more of the attributes using respective adaptive mixtures of the estimated attribute values.
    • 提供了一种用于共享机器学习的系统和方法。 该方法包括向包括在机器学习系统中的多个代理提供模型。 该模型指定代理行为的事件的属性和属性值数据类型。 该方法还包括在事件的实例期间接收代理提供的输入。 代理提供的输入包括与属性值数据类型一致的估计属性值。 该方法还包括响应于从估计的属性值学习的至少一个地面真值来确定至少一些代理的专业知识权重。 该方法另外包括使用估计的属性值的各自的自适应混合来确定一个或多个属性的估计值。