Learning to Transfer Examples for Partial Domain Adaptation
CVPR, pp. 2985-2994, 2019.
Domain adaptation is critical for learning in new and unseen environments. With domain adversarial training, deep networks can learn disentangled and transferable features that effectively diminish the dataset shift between the source and target domains for knowledge transfer. In the era of Big Data, the ready availability of large-scale ...More
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