Securing Multi-Source Domain Adaptation With Global and Domain-Wise Privacy Demands

Making available a large size of training data for deep learning models and preserving data privacy are two ever-growing concerns in the machine learning community. Multi-source domain adaptation (MDA) leverages the data information from different domains and aggregates them to improve the performan...

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Veröffentlicht in:	IEEE transactions on knowledge and data engineering 2024-12, Vol.36 (12), p.9235-9248
Hauptverfasser:	Chai, Shuwen, Xiao, Yutang, Liu, Feng, Zhu, Jian, Zhou, Yuan
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Data models data privacy and security Differential privacy Feature extraction Multi-source domain adaptation Privacy Protection Training
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