26 citations · 122 across the 33 of their papers we have counts for
6 papers · 1 filter
Decentralized convex optimization over time-varying graphs: a survey
Alexander Rogozin, Alexander Gasnikov, Aleksander Beznosikov +1
Decentralized optimization over time-varying networks has a wide range of applications in distributed learning, signal processing and various distributed control problems. The agen…
The Mirror-Prox Sliding Method for Non-smooth decentralized saddle-point problems
Ilya Kuruzov, Alexander Rogozin, Demyan Yarmoshik +1
The saddle-point optimization problems have a lot of practical applications. This paper focuses on such non-smooth problems in decentralized case. This work contains generalization…
Decentralized Strongly-Convex Optimization with Affine Constraints: Primal and Dual Approaches
Alexander Rogozin, Demyan Yarmoshik, Ksenia Kopylova +1
Decentralized optimization is a common paradigm used in distributed signal processing and sensing as well as privacy-preserving and large-scale machine learning. It is assumed that…
Decentralized Saddle-Point Problems with Different Constants of Strong Convexity and Strong Concavity
Dmitriy Metelev, Alexander Rogozin, Alexander Gasnikov +1
Large-scale saddle-point problems arise in such machine learning tasks as GANs and linear models with affine constraints. In this paper, we study distributed saddle-point problems…
Decentralized convex optimization under affine constraints for power systems control
Demyan Yarmoshik, Alexander Rogozin, Oleg. O. Khamisov +2
Modern power systems are now in continuous process of massive changes. Increased penetration of distributed generation, usage of energy storage and controllable demand require intr…
A General Framework for Distributed Partitioned Optimization
Savelii Chezhegov, Anton Novitskii, Alexander Rogozin +3
Decentralized optimization is widely used in large scale and privacy preserving machine learning and various distributed control and sensing systems. It is assumed that every agent…