Summary of Fedmoe: Personalized Federated Learning Via Heterogeneous Mixture Of Experts, by Hanzi Mei et al.
FedMoE: Personalized Federated Learning via Heterogeneous Mixture of Expertsby Hanzi Mei, Dongqi Cai, Ao Zhou,…
FedMoE: Personalized Federated Learning via Heterogeneous Mixture of Expertsby Hanzi Mei, Dongqi Cai, Ao Zhou,…
Federated Clustering: An Unsupervised Cluster-Wise Training for Decentralized Data Distributionsby Mirko Nardi, Lorenzo Valerio, Andrea…
Security Assessment of Hierarchical Federated Deep Learningby D Alqattan, R Sun, H Liang, G Nicosia,…
Federated Learning of Large ASR Models in the Real Worldby Yonghui Xiao, Yuxin Ding, Changwan…
FedKBP: Federated dose prediction framework for knowledge-based planning in radiation therapyby Jingyun Chen, Martin King,…
FEDKIM: Adaptive Federated Knowledge Injection into Medical Foundation Modelsby Xiaochen Wang, Jiaqi Wang, Houping Xiao,…
Federated Frank-Wolfe Algorithmby Ali Dadras, Sourasekhar Banerjee, Karthik Prakhya, Alp YurtseverFirst submitted to arxiv on:…
Sequential Federated Learning in Hierarchical Architecture on Non-IID Datasetsby Xingrun Yan, Shiyuan Zuo, Rongfei Fan,…
Mitigating Noise Detriment in Differentially Private Federated Learning with Model Pre-trainingby Huitong Jin, Yipeng Zhou,…
Byzantine-resilient Federated Learning Employing Normalized Gradients on Non-IID Datasetsby Shiyuan Zuo, Xingrun Yan, Rongfei Fan,…