Li Liu

Heterogeneity‐Aware Federated Learning via Heterogeneity Identification and Adaptive Optimization

This work proposes an integrated framework that combines parameter‐oriented heterogeneity identification with adaptive optimization, and introduces an attention‐guided prior loss that imposes stronger constraints on heterogeneity‐sensitive parameter regions while preserving local adaptability in less sensitive regions.