Prox-ITEM achieves the minimax-optimal distance-to-solution rate among span-based first-order methods for smooth strongly convex composite problems, with Prox-TMM as its stationary limit matching TMM rates.
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Local updates accelerate the DIGing algorithm in distributed optimization, with maximal gains from two updates that depend on network spectral properties.
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An optimal first-order method for smooth and strongly convex composite optimization and its stationary limit
Prox-ITEM achieves the minimax-optimal distance-to-solution rate among span-based first-order methods for smooth strongly convex composite problems, with Prox-TMM as its stationary limit matching TMM rates.
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Local Updates in Distributed Optimization: Provable Acceleration and Topology Effects
Local updates accelerate the DIGing algorithm in distributed optimization, with maximal gains from two updates that depend on network spectral properties.