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On the Model-Agnostic Multi-Source-Free Unsupervised Domain Adaptation
March 5, 2024, 2:42 p.m. | Jiangbo Pei, Ruizhe Li, Qingchao Chen
cs.LG updates on arXiv.org arxiv.org
Abstract: Multi-Source-Free Unsupervised Domain Adaptation (MSFDA) aims to transfer knowledge from multiple well-labeled source domains to an unlabeled target domain, using source models instead of source data. Existing MSFDA methods limited that each source domain provides only a single model, with a uniform structure. This paper introduces a new MSFDA setting: Model-Agnostic Multi-Source-Free Unsupervised Domain Adaptation (MMDA), allowing diverse source models with varying architectures, without quantitative restrictions. While MMDA holds promising potential, incorporating numerous source models …
abstract arxiv cs.lg data domain domain adaptation domains free knowledge model-agnostic multiple paper source data transfer type uniform unsupervised
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