# Distributed Saddle-Point Problems: Lower Bounds, Near-Optimal and Robust Algorithms

@inproceedings{Beznosikov2020DistributedSP, title={Distributed Saddle-Point Problems: Lower Bounds, Near-Optimal and Robust Algorithms}, author={Aleksandr Beznosikov and Valentin Samokhin and Alexander V. Gasnikov}, year={2020} }

This paper focuses on the distributed optimization of stochastic saddle point problems. The first part of the paper is devoted to lower bounds for the cenralized and decentralized distributed methods for smooth (strongly) convex-(strongly) concave saddle-point problems as well as the near-optimal algorithms by which these bounds are achieved. Next, we present a new federated algorithm for cenralized distributed saddle point problems – Extra Step Local SGD. Theoretical analysis of the new method…

## 11 Citations

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