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cs.LG2026
Coding-Enforced Resilient and Secure Aggregation for Hierarchical Federated Learning
Shudi Weng, Ming Xiao, Mikael Skoglund
Hierarchical federated learning (HFL) has emerged as an effective paradigm to enhance link quality between clients and the server. However, ensuring model accuracy while preserving…
cs.LG2025
Heterogeneity-Aware Client Sampling for Optimal and Efficient Federated Learning
Shudi Weng, Chao Ren, Ming Xiao +1
Federated learning (FL) commonly involves clients with diverse communication and computational capabilities. Such heterogeneity can significantly distort the optimization dynamics…