Sébastien Bubeck

Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks

In this paper, we determine the optimal convergence rates for strongly convex and smooth distributed optimization in two settings: centralized and decentralized communications over a network. For centralized (i.e. master/slave) algorithms, we show that distributing Nesterov’s accelerated gradient de…