The paper proposes DSWM and ASWM, two Stackelberg-game-inspired algorithms that reweight node contributions in federated learning, and reports modest AUC gains for small-data nodes on three MedMNIST datasets.
Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare
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Fair Distributed Machine Learning with Imbalanced Data as a Stackelberg Evolutionary Game
The paper proposes DSWM and ASWM, two Stackelberg-game-inspired algorithms that reweight node contributions in federated learning, and reports modest AUC gains for small-data nodes on three MedMNIST datasets.