Cross-Domain Metric Learning Based on Information Theory

Abstract

Supervised metric learning plays a substantial role in statistical classification. Conventional metric learning algorithms have limited utility when the training data and testing data are drawn from related but different domains (i.e., source domain and target domain). Although this issue has got some progress in feature-based transfer learning, most of the… (More)

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@inproceedings{Wang2014CrossDomainML, title={Cross-Domain Metric Learning Based on Information Theory}, author={Hao Wang and Wei Eric Wang and Chen Zhang and Fanjiang Xu}, booktitle={AAAI}, year={2014} }