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Qingsong Wei

2 accepted papers

2025

Look Back for More: Harnessing Historical Sequential Updates for Personalized Federated Adapter Tuning

AAAI 2025technical

Personalized federated learning (PFL) studies effective model personalization to address the data heterogeneity issue among clients in traditional federated learning (FL). Existing PFL approaches mainly generate personalized models by relying solely on the clients' latest updated models while ignori…

Cited by 0SourcePDFScholar
2024

An Aggregation-Free Federated Learning for Tackling Data Heterogeneity

CVPR 2024poster

The performance of Federated Learning (FL) hinges on the effectiveness of utilizing knowledge from distributed datasets. Traditional FL methods adopt an aggregate-then-adapt framework where clients update local models based on a global model aggregated by the server from the previous training round.…

Cited by 42SourcePDFScholar