Open Set Domain Adaptation: Theoretical Bound and Algorithm

The aim of unsupervised domain adaptation is to leverage the knowledge in a labeled (source) domain to improve a model's learning performance with an unlabeled (target) domain-the basic strategy being to mitigate the effects of discrepancies between the two distributions. Most existing algorith...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2021-10, Vol.32 (10), p.4309-4322
Hauptverfasser:	Fang, Zhen, Lu, Jie, Liu, Feng, Xuan, Junyu, Zhang, Guangquan
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation Algorithms Classifiers Domain adaptation Domains Learning Learning systems machine learning open set recognition Prediction algorithms Random variables Support vector machines Target recognition Task analysis Training transfer learning
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