The authors generalize PBACC to tensor data and derive secure aggregation and secure training schemes for centralized and decentralized learning, with experiments on CNN, VAE, and Cox models.
Straggler mitigation in distributed matrix multiplication: Fundamental limits and optimal coding,
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Privacy-aware Berrut Approximated Coded Computing applied to general distributed learning
The authors generalize PBACC to tensor data and derive secure aggregation and secure training schemes for centralized and decentralized learning, with experiments on CNN, VAE, and Cox models.