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Application of Optimal Inexact Second-Order Acceleration to Distributed Stochastic Optimization under Statistical Similarity
We consider distributed stochastic convex optimization with a fixed budget of $N$ independent samples split among $m$ workers. Sample average approximation reduces the problem to a regularized finite-sum problem whose local Hessians are statistically similar. This allows the Hessian of the local obj
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