Towards Fair, Robust and Efficient Client Contribution Evaluation in Federated Learning

Ähnliche Einträge

• Identifying the Truth of Global Model: A Generic Solution to Defend Against Byzantine and Backdoor Attacks in Federated Learning (full version)
  von: Ebron, Sheldon C., et al.
  Veröffentlicht: (2023)
• Toward Malicious Clients Detection in Federated Learning
  von: Dou, Zhihao, et al.
  Veröffentlicht: (2025)
• FLARE: Adaptive Multi-Dimensional Reputation for Robust Client Reliability in Federated Learning
  von: Younesi, Abolfazl, et al.
  Veröffentlicht: (2025)
• Celtibero: Robust Layered Aggregation for Federated Learning
  von: Molina-Coronado, Borja
  Veröffentlicht: (2024)
• Communication-Efficient and Differentially Private Vertical Federated Learning with Zeroth-Order Optimization
  von: Zhang, Jianing, et al.
  Veröffentlicht: (2025)