Distributed Saddle-Point Problems Under Data Similarity

no code implementations • NeurIPS 2021 • Aleksandr Beznosikov, Gesualdo Scutari, Alexander Rogozin, Alexander Gasnikov

We study solution methods for (strongly-)convex-(strongly)-concave Saddle-Point Problems (SPPs) over networks of two type--master/workers (thus centralized) architectures and mesh (thus decentralized) networks.

Distributed Saddle-Point Problems Under Similarity

1 code implementation • 22 Jul 2021 • Aleksandr Beznosikov, Gesualdo Scutari, Alexander Rogozin, Alexander Gasnikov

We study solution methods for (strongly-)convex-(strongly)-concave Saddle-Point Problems (SPPs) over networks of two type - master/workers (thus centralized) architectures and meshed (thus decentralized) networks.

ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks

no code implementations • 18 Feb 2021 • Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Alexander Rogozin, Alexander Gasnikov

We propose ADOM - an accelerated method for smooth and strongly convex decentralized optimization over time-varying networks.

Decentralized Distributed Optimization for Saddle Point Problems

no code implementations • 15 Feb 2021 • Alexander Rogozin, Alexander Beznosikov, Darina Dvinskikh, Dmitry Kovalev, Pavel Dvurechensky, Alexander Gasnikov

We consider distributed convex-concave saddle point problems over arbitrary connected undirected networks and propose a decentralized distributed algorithm for their solution.

Distributed Optimization Optimization and Control Distributed, Parallel, and Cluster Computing