6 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Trustworthy Personalized Bayesian Federated Learning via Posterior Fine-Tune
Mengen Luo, Chi Xu, Ercan Engin Kuruoglu
Performance degradation owing to data heterogeneity and low output interpretability are the most significant challenges faced by federated learning in practical applications. Perso…
cs.LG2024
Bayesian Neural Network For Personalized Federated Learning Parameter Selection
Mengen Luo, Ercan Engin Kuruoglu
Federated learning's poor performance in the presence of heterogeneous data remains one of the most pressing issues in the field. Personalized federated learning departs from the c…
cs.LG2022★ 6 cited
Deep Leakage from Model in Federated Learning
Zihao Zhao, Mengen Luo, Wenbo Ding
Distributed machine learning has been widely used in recent years to tackle the large and complex dataset problem. Therewith, the security of distributed learning has also drawn in…