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Distributed Saddle-Point Problems Under Similarity

July 2021

Decentralized and Personalized Federated Learning

July 2021

Optimal Decentralized Algorithms for Saddle Point Problems over Time-Varying Networks

July 2021

One-Point Gradient-Free Methods for Composite Optimization with Applications to Distributed Optimization

Ivan Stepanov, Artyom Voronov, Aleksandr Beznosikov, Alexander Gasnikov

July 2021

Decentralized Local Stochastic Extra-Gradient for Variational Inequalities

June 2021

Decentralized Personalized Federated Min-Max Problems

Aleksandr Beznosikov, Vadim Sushko, Abdurakhmon Sadiev, Alexander Gasnikov

June 2021

One-Point Gradient-Free Methods for Smooth and Non-Smooth Saddle-Point Problems

Aleksandr Beznosikov, Vasilii Novitskii and Alexander Gasnikov

MOTOR 2021 (Irkutsk, Russia), LNCS series

March 2021

Solving smooth min-min and min-max problems by mixed oracle algorithms

Egor Gladin, Abdurakhmon Sadiev, Alexander Gasnikov, Pavel Dvurechensky, Aleksandr Beznosikov, Mohammad Alkousa

MOTOR 2021 (Irkutsk, Russia), CCIS series

March 2021

Distributed Saddle-Point Problems: Lower Bounds, Optimal Algorithms and Federated GANs

Aleksandr Beznosikov, Valentin Samokhin and Alexander Gasnikov

February 2021

Decentralized Distributed Optimization for Saddle Point Problems

Alexander Rogozin, Aleksandr Beznosikov, Darina Dvinskikh, Dmitry Kovalev, Pavel Dvurechensky and Alexander Gasnikov

February 2021

Recent theoretical advances in decentralized distributed convex optimization

LNCS series

November 2020

Zeroth-Order Algorithms for Smooth Saddle-Point Problems

Abdurakhmon Sadiev, Aleksandr Beznosikov, Pavel Dvurechensky, Alexander Gasnikov

MOTOR 2021 (Irkutsk, Russia), CCIS series

September 2020

Linearly Convergent Gradient-Free Methods for Minimization of Symmetric Parabolic Approximation

Aleksandra Bazarova, Aleksandr Beznosikov and Alexander Gasnikov

September 2020

Gradient-Free Methods for Saddle-Point Problem

Aleksandr Beznosikov, Abdurakhmon Sadiev and Alexander Gasnikov

MOTOR 2020 (Novosibirsk, Russia), CCIS series

May 2020

On Biased Compression for Distributed Learning

Aleksandr Beznosikov, Samuel Horváth, Peter Richtárik and Mher Safaryan

Oral talk at NeurIPS 2020 Workshop on Scalability, Privacy and Security in Federated Learning

Febuary 2020

Derivative-Free Method For Decentralized Distributed Non-Smooth Optimization

Aleksandr Beznosikov, Eduard Gorbunov and Alexander Gasnikov

IFAC World Congress 2020 (Berlin, Germany), IFAC Papers Online

November 2019

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