Federated Unsupervised Learning

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

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Most implemented papers archive 2025-07-28

3 shown of 3 papers with code (5 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• ADEPT: Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning
  19 Feb 2024 1 repository listed
  Though there has been a plethora of algorithms proposed for personalized supervised learning, discovering the structure of local data through personalized unsupervised learning is less explored.
• Divergence-aware Federated Self-Supervised Learning
  9 Apr 2022 1 repository listed
  Using the framework, our study uncovers unique insights of FedSSL: 1) stop-gradient operation, previously reported to be essential, is not always necessary in FedSSL; 2) retaining local knowledge of clients in FedSSL is…
• Collaborative Unsupervised Visual Representation Learning from Decentralized Data
  14 Aug 2021 1 repository listed Syntology ran 2 of 5 samples · 3 unverified
  In this framework, each party trains models from unlabeled data independently using contrastive learning with an online network and a target network.

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-25.