2023
DOI: 10.48550/arxiv.2303.16154
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Guided Transfer Learning

Abstract: Machine learning requires exuberant amounts of data and computation. Also, models require equally excessive growth in the number of parameters. It is, therefore, sensible to look for technologies that reduce these demands on resources. Here, we propose an approach called guided transfer learning. Each weight and bias in the network has its own guiding parameter that indicates how much this parameter is allowed to change while learning a new task. Guiding parameters are learned during an initial scouting proces… Show more

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