Domain Adversarial Reinforcement Learning for Partial Domain Adaptation

Partial domain adaptation aims to transfer knowledge from a label-rich source domain to a label-scarce target domain (i.e., the target categories are a subset of the source ones), which relaxes the common assumption in traditional domain adaptation that the label space is fully shared across differe...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2022-02, Vol.33 (2), p.539-553
Hauptverfasser:	Chen, Jin, Wu, Xinxiao, Duan, Lixin, Gao, Shenghua
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation Adversarial learning Benchmark testing Computer science Domains Feature extraction Games Generators Knowledge management Learning Learning systems Machine learning partial domain adaptation Reinforcement Reinforcement learning
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