Showing cs.LGShow all
2 papers · 1 filter
cs.LG2025
Rethinking the Backbone in Class Imbalanced Federated Source Free Domain Adaptation: The Utility of Vision Foundation Models
Kosuke Kihara, Junki Mori, Taiki Miyagawa +1
Federated Learning (FL) offers a framework for training models collaboratively while preserving data privacy of each client. Recently, research has focused on Federated Source-Free…
cs.LG2024
Federated Source-free Domain Adaptation for Classification: Weighted Cluster Aggregation for Unlabeled Data
Junki Mori, Kosuke Kihara, Taiki Miyagawa +3
Federated learning (FL) commonly assumes that the server or some clients have labeled data, which is often impractical due to annotation costs and privacy concerns. Addressing this…