2026
FedAdamom: Adaptive Momentum for Improved Generalization in Federated Optimization
CVPR 2026
Federated learning (FL) has emerged as a widely adopted training paradigm for privacy-preserving machine learning. Despite the past success of SGD-based methods, they still suffer from severe data heterogeneity and the lack of adaptivity in practical applications. While several adaptive federated op