Totoro+ is a DHT-based fully decentralized FL system with locality-aware multi-ring P2P structure, pub/sub forest, and game-theoretic path planning that claims O(log N) hops and 1.2-14x speedup for many concurrent applications on edge nodes.
Federated evalua- tion and tuning for on-device personalization: System design & applications.arXiv preprint arXiv:2102.08503
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Introduces FedHybrid and FedNewton for DP federated M-estimation, with finite-sample MSE bounds, minimax lower bound, and evaluations on vision datasets.
SecureAFL secures asynchronous federated learning against poisoning attacks by detecting anomalous updates, estimating missing client contributions, and using Byzantine-robust aggregation.
citing papers explorer
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Totoro$^+$: An Adaptive and Scalable Edge Federated Learning System
Totoro+ is a DHT-based fully decentralized FL system with locality-aware multi-ring P2P structure, pub/sub forest, and game-theoretic path planning that claims O(log N) hops and 1.2-14x speedup for many concurrent applications on edge nodes.
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Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning
Introduces FedHybrid and FedNewton for DP federated M-estimation, with finite-sample MSE bounds, minimax lower bound, and evaluations on vision datasets.
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SecureAFL: Secure Asynchronous Federated Learning
SecureAFL secures asynchronous federated learning against poisoning attacks by detecting anomalous updates, estimating missing client contributions, and using Byzantine-robust aggregation.