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cs.LG2024
Privacy-Preserving Federated Learning via Dataset Distillation
ShiMao Xu, Xiaopeng Ke, Xing Su +4
Federated Learning (FL) allows users to share knowledge instead of raw data to train a model with high accuracy. Unfortunately, during the training, users lose control over the kno…
cs.LG2024
CoAst: Validation-Free Contribution Assessment for Federated Learning based on Cross-Round Valuation
Hao Wu, Likun Zhang, Shucheng Li +2
In the federated learning (FL) process, since the data held by each participant is different, it is necessary to figure out which participant has a higher contribution to the model…