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Found 2 papers, 1 papers with code
One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them
We investigate the impact of communication constraint, $B$, on the expected error and derive a tight lower bound on the error achievable by any algorithm.
Distributed Voting/Ranking with Optimal Number of States per Node
Considering a network with $n$ nodes, where each node initially votes for one (or more) choices out of $K$ possible choices, we present a Distributed Multi-choice Voting/Ranking (DMVR) algorithm to determine either the choice with maximum vote (the voting problem) or to rank all the choices in terms of their acquired votes (the ranking problem).
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