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Population Scaling or Data Dilution? Dynamics of Local Topology Evolution in Decentralized Learning
Scaling decentralized learning changes not only the number of clients $N$, but also the dynamics of information propagation and consensus. We argue that the effect of increasing $N$ cannot be understood in isolation, because data allocation, topology-dependent mixing, and communication capacity may
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