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Transfer learning and domain adaptation using distributable data models
Transfer learning and domain adaptation using distributable data models
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机译:基于分布式数据模型的迁移学习与领域适应
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摘要
A system for transfer learning and domain adaptation using distributable data models is provided, comprising a network-connected distributable model configured to serve instances of a plurality of distributable models; and a directed computation graph module configured to receive at least an instance of at least one of the distributable models from the network-connected computing system, create a second dataset from machine learning performed by a transfer engine, train the instance of the distributable model with the second dataset, and generate an update report based at least in part by updates to the instance of the distributable model.
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