Si-Te Li

Semantic-Aware Differentially Private and Trust-Driven Robust Federated Optimization for Multi-Center Medical Image Analysis

Federated learning enables hospitals to jointly train diagnostic models without sharing raw medical images, yet multi-center deployment remains vulnerable to site-dependent semantic shifts, privacy leakage, and unreliable model updates. This paper presents a two-level optimization framework. At the client level, SemaDi...