gossip-learning

A matched-protocol comparison of synchronous ring gossip, FedAvg, local and centralized training for LSTM failure detectors on the NASA C-MAPSS turbofan benchmark, showing gossip as a practical serverless alternative to federated averaging that matches FedAvg performance without a coordinator.

This paper provides convergence theory for knowledge distillation in asynchronous peer-to-peer gossip learning networks, demonstrating that it contracts function disagreement and analyzing theoretical convergence rates.