DFedReweighting is a unified reweighting method for decentralized federated learning that customizes aggregation via target metrics and strategies to improve fairness, Byzantine robustness, and other objectives while proving linear convergence under standard assumptions.
Federated learning over wireless device-to-device networks: Algo- rithms and convergence analysis.IEEE Journal on Selected Areas in Communications, 39(12):3723–3741, 2021
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DFedReweighting: A Unified Framework for Objective-Oriented Reweighting in Decentralized Federated Learning
DFedReweighting is a unified reweighting method for decentralized federated learning that customizes aggregation via target metrics and strategies to improve fairness, Byzantine robustness, and other objectives while proving linear convergence under standard assumptions.