AI RESEARCH
Gaussian Approximation and Multiplier Bootstrap for Federated Linear Stochastic Approximation
arXiv CS.LG
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ArXi:2605.19629v1 Announce Type: cross In this paper, we establish Berry-Esseen-type bounds for federated linear stochastic approximation (LSA). Our results provide the first federated Gaussian approximations for LSA that explicitly capture communication-computation trade-offs and heterogeneity-aware error terms, quantifying the effects of local step size, number of local updates, and heterogeneity on convergence rates.