Summary of A Robust Federated Learning Framework For Undependable Devices at Scale, by Shilong Wang et al.
A Robust Federated Learning Framework for Undependable Devices at Scaleby Shilong Wang, Jianchun Liu, Hongli…
Summary of Asymmetrical Reciprocity-based Federated Learning For Resolving Disparities in Medical Diagnosis, by Jiaqi Wang et al.
Asymmetrical Reciprocity-based Federated Learning for Resolving Disparities in Medical Diagnosisby Jiaqi Wang, Ziyi Yin, Quanzeng…
Summary of Federated Hybrid Training and Self-adversarial Distillation: Towards Robust Edge Networks, by Yu Qiao et al.
Federated Hybrid Training and Self-Adversarial Distillation: Towards Robust Edge Networksby Yu Qiao, Apurba Adhikary, Kitae…
Summary of Fedcfa: Alleviating Simpson’s Paradox in Model Aggregation with Counterfactual Federated Learning, by Zhonghua Jiang et al.
FedCFA: Alleviating Simpson’s Paradox in Model Aggregation with Counterfactual Federated Learningby Zhonghua Jiang, Jimin Xu,…
Summary of Fedvck: Non-iid Robust and Communication-efficient Federated Learning Via Valuable Condensed Knowledge For Medical Image Analysis, by Guochen Yan et al.
FedVCK: Non-IID Robust and Communication-Efficient Federated Learning via Valuable Condensed Knowledge for Medical Image Analysisby…
Summary of Handling Spatial-temporal Data Heterogeneity For Federated Continual Learning Via Tail Anchor, by Hao Yu et al.
Handling Spatial-Temporal Data Heterogeneity for Federated Continual Learning via Tail Anchorby Hao Yu, Xin Yang,…
Summary of Gefl: Model-agnostic Federated Learning with Generative Models, by Honggu Kang et al.
GeFL: Model-Agnostic Federated Learning with Generative Modelsby Honggu Kang, Seohyeon Cha, Joonhyuk KangFirst submitted to…
Summary of An Empirical Analysis Of Federated Learning Models Subject to Label-flipping Adversarial Attack, by Kunal Bhatnagar and Sagana Chattanathan and Angela Dang and Bhargav Eranki and Ronnit Rana and Charan Sridhar and Siddharth Vedam and Angie Yao and Mark Stamp
An Empirical Analysis of Federated Learning Models Subject to Label-Flipping Adversarial Attackby Kunal Bhatnagar, Sagana…
Summary of Fedgig: Graph Inversion From Gradient in Federated Learning, by Tianzhe Xiao et al.
FedGIG: Graph Inversion from Gradient in Federated Learningby Tianzhe Xiao, Yichen Li, Yining Qi, Haozhao…
Summary of Fedtlu: Federated Learning with Targeted Layer Updates, by Jong-ik Park and Carlee Joe-wong
FedTLU: Federated Learning with Targeted Layer Updatesby Jong-Ik Park, Carlee Joe-WongFirst submitted to arxiv on:…