3 papers
cs.LG2025
GuardFed: A Trustworthy Federated Learning Framework Against Dual-Facet Attacks
Yanli Li, Yanan Zhou, Zhongliang Guo +6
Federated learning (FL) enables privacy-preserving collaborative model training but remains vulnerable to adversarial behaviors that compromise model utility or fairness across sen…
cs.LG2024
CAKD: A Correlation-Aware Knowledge Distillation Framework Based on Decoupling Kullback-Leibler Divergence
Zao Zhang, Huaming Chen, Pei Ning +2
In knowledge distillation, a primary focus has been on transforming and balancing multiple distillation components. In this work, we emphasize the importance of thoroughly examinin…
cs.LG2024
Holistic Evaluation Metrics: Use Case Sensitive Evaluation Metrics for Federated Learning
Yanli Li, Jehad Ibrahim, Huaming Chen +2
A large number of federated learning (FL) algorithms have been proposed for different applications and from varying perspectives. However, the evaluation of such approaches often r…