Prototype Similarity Distillation for Communication-Efficient Federated Unsupervised Representation Learning
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DOI: 10.1109/tkde.2024.3386712
Abstract: Federated unsupervised representation learning aims at leveraging unlabeled data from multiple parties to learn visual representations without compromising the data privacy and tackle the non-IID challenge by aligning diverse representation spaces. However, model heterogeneity and… read more here.
Keywords: unsupervised representation; representation; representation learning; federated unsupervised ... See more keywords