Project: Efficient sampling and aggregation of non-iid clients for federated learning

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TMLR: Optimal Client Sampling for Federated Learning TMLR: Optimal Client Sampling for Federated Learning
Experimenting With Normalization Layers in Federated Learning on Non IID Scenarios Experimenting With Normalization Layers in Federated Learning on Non IID Scenarios
Federated Learning With Non IID Data in Wireless Networks Federated Learning With Non IID Data in Wireless Networks
Non IID Federated Learning With Sharper Risk Bound Non IID Federated Learning With Sharper Risk Bound
FedBalancer: Data and Pace Control for Efficient Federated Learning on Heterogeneous Clients FedBalancer: Data and Pace Control for Efficient Federated Learning on Heterogeneous Clients
[CVPR2024] Communication Efficient Federated Learning with Accelerated Client Gradient [CVPR2024] Communication Efficient Federated Learning with Accelerated Client Gradient
Improving Accuracy and Convergence in Group Based Federated Learning on Non IID Data Improving Accuracy and Convergence in Group Based Federated Learning on Non IID Data
Communication-Efficient Federated Data Augmentation on Non-IID Data Communication-Efficient Federated Data Augmentation on Non-IID Data