Cross-Domain Metric and Multiple Kernel Learning Based on Information Theory

Neural Computation, pp. 820-855, 2018.

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Abstract:

Learning an appropriate distance metric plays a substantial role in the success of many learning machines. Conventional metric learning algorithms have limited utility when the training and test samples are drawn from related but different domains (i.e., source domain and target domain). In this letter, we propose two novel metric learnin...More

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