Comprehensive experiments on three benchmark datasets Office-31, Office-Home, and Caltech-Office corroborate the effectiveness of the proposed approach in addressing different partial transfer learning tasks.Mohsen KheirandishfardFariba ZohrizadehFarhad Kamangar会议论文...
Domain-invariant adversarial learning with conditional distribution alignment for unsupervised domain adaptation Unsupervised domain adaption aims to reduce the divergence between the source domain and the target domain. The final objective is to learn domain-invarian... X Wang,B Sun,H Dong - 《Iet ...
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The conventional approach involves automatic extraction and alignment of the representations of source and target domains globally. One limitation of this approach is that it tends to neglect the differences between classes: representations of certain classes can be more easily extracted and aligned ...
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