2 papers
cs.LG2025
Achieving Distributive Justice in Federated Learning via Uncertainty Quantification
Alycia Carey, Xintao Wu
Client-level fairness metrics for federated learning are used to ensure that all clients in a federation either: a) have similar final performance on their local data distributions…
cs.LG2025
A Client-level Assessment of Collaborative Backdoor Poisoning in Non-IID Federated Learning
Phung Lai, Guanxiong Liu, NhatHai Phan +3
Federated learning (FL) enables collaborative model training using decentralized private data from multiple clients. While FL has shown robustness against poisoning attacks with ba…