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Found 3 papers, 2 papers with code
Decentralized Sporadic Federated Learning: A Unified Methodology with Generalized Convergence Guarantees
Decentralized Federated Learning (DFL) has received significant recent research attention, capturing settings where both model updates and model aggregations -- the two key FL processes -- are conducted by the clients.
The Impact of Adversarial Node Placement in Decentralized Federated Learning Networks
This paper addresses this gap by analyzing the performance of decentralized FL for various adversarial placement strategies when adversaries can jointly coordinate their placement within a network.
On the Effects of Data Heterogeneity on the Convergence Rates of Distributed Linear System Solvers
Using this notion, we bound and compare the convergence rates of the studied algorithms and capture the effects of both cross-machine and local data heterogeneity on these quantities.
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