Summary of Dynamicfl: Federated Learning with Dynamic Communication Resource Allocation, by Qi Le et al.
DynamicFL: Federated Learning with Dynamic Communication Resource Allocationby Qi Le, Enmao Diao, Xinran Wang, Vahid…
DynamicFL: Federated Learning with Dynamic Communication Resource Allocationby Qi Le, Enmao Diao, Xinran Wang, Vahid…
Some Results on Neural Network Stability, Consistency, and Convergence: Insights into Non-IID Data, High-Dimensional Settings,…
FedModule: A Modular Federated Learning Frameworkby Chuyi Chen, Zhe Zhang, Yanchao ZhaoFirst submitted to arxiv…
Unlocking the Potential of Model Calibration in Federated Learningby Yun-Wei Chu, Dong-Jun Han, Seyyedali Hosseinalipour,…
Active-Passive Federated Learning for Vertically Partitioned Multi-view Databy Jiyuan Liu, Xinwang Liu, Siqi Wang, Xingchen…
Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated…
Wind turbine condition monitoring based on intra- and inter-farm federated learningby Albin Grataloup, Stefan Jonas,…
VFLGAN-TS: Vertical Federated Learning-based Generative Adversarial Networks for Publication of Vertically Partitioned Time-Series Databy Xun…
CoAst: Validation-Free Contribution Assessment for Federated Learning based on Cross-Round Valuationby Hao Wu, Likun Zhang,…
Robust Federated Finetuning of Foundation Models via Alternating Minimization of LoRAby Shuangyi Chen, Yue Ju,…