A Damped Newton Method Achieves Global O(1/K²) and Local Quadratic Convergence Rate, Slavomír Hanzely, Dmitry Kamzolov, Dmitry Pasechnyuk, Alexander Gasnikov, Peter Richtárik, Martin Takáč
Martin Takac

Decentralized personalized federated learning: Lower bounds and optimal algorithm for all personalization modes, Abdurakhmon Sadiev, Ekaterina Borodich, Aleksandr Beznosikov, Darina Dvinskikh, Saveliy Chezhegov, Rachael Tappenden, Martin Takac, Alexander Gasnikov
Martin Takac

A Damped Newton Method Achieves Global O(1/K²) and Local Quadratic Convergence Rate, Slavomír Hanzely, Dmitry Kamzolov, Dmitry Pasechnyuk, Alexander Gasnikov, Peter Richtárik, Martin Takáč
Machine Learning Faculty Publications

Hyperfast second-order local solvers for efficient statistically preconditioned distributed optimization, Pavel Dvurechensky, Dmitry Kamzolov, Aleksandr Lukashevich, Soomin Lee, Erik Ordentlich, César A. Uribe, Alexander Gasnikov
Machine Learning Faculty Publications

Decentralized personalized federated learning: Lower bounds and optimal algorithm for all personalization modes, Abdurakhmon Sadiev, Ekaterina Borodich, Aleksandr Beznosikov, Darina Dvinskikh, Saveliy Chezhegov, Rachael Tappenden, Martin Takac, Alexander Gasnikov
Machine Learning Faculty Publications

Exploiting higher-order derivatives in convex optimization methods, Dmitry Kamzolov, Alexander Gasnikov, Pavel Dvurechensky, Artem Agafonov, Martin Takac
Martin Takac

Exploiting higher-order derivatives in convex optimization methods, Dmitry Kamzolov, Alexander Gasnikov, Pavel Dvurechensky, Artem Agafonov, Martin Takac
Machine Learning Faculty Publications

On Scaled Methods for Saddle Point Problems, Aleksandr Beznosikov, Aibek Alanov, Dmitry Kovalev, Martin Takac, Alexander Gasnikov
Martin Takac

Algorithm for Constrained Markov Decision Process with Linear Convergence, Egor Gladin, Maksim Lavrik-Karmazin, Karina Zainullina, Varvara Rudenko, Alexander Gasnikov, Martin Takac
Martin Takac

FLECS: A Federated Learning Second-Order Framework via Compression and Sketching, Artem Agafonov, Dmitry Kamzolov, Rachael Tappenden, Alexander Gasnikov, Martin Takac
Martin Takac

Inexact Tensor Methods and Their Application to Stochastic Convex Optimization, Artem Agafonov, Dmitry Kamzolov, Pavel Dvurechensky, Alexander Gasnikov, Martin Takac
Martin Takac

Algorithm for Constrained Markov Decision Process with Linear Convergence, Egor Gladin, Maksim Lavrik-Karmazin, Karina Zainullina, Varvara Rudenko, Alexander Gasnikov, Martin Takac
Machine Learning Faculty Publications

FLECS: A Federated Learning Second-Order Framework via Compression and Sketching, Artem Agafonov, Dmitry Kamzolov, Rachael Tappenden, Alexander Gasnikov, Martin Takac
Machine Learning Faculty Publications

On Scaled Methods for Saddle Point Problems, Aleksandr Beznosikov, Aibek Alanov, Dmitry Kovalev, Martin Takac, Alexander Gasnikov
Machine Learning Faculty Publications

Recent Theoretical Advances in Non-Convex Optimization, Marina Danilova, Pavel Dvurechensky, Alexander Gasnikov, Eduard Gorbunov, Sergey Guminov, Dmitry Kamzolov, Innokentiy Shibaev
Machine Learning Faculty Publications

Inexact Tensor Methods and Their Application to Stochastic Convex Optimization, Artem Agafonov, Dmitry Kamzolov, Pavel Dvurechensky, Alexander Gasnikov, Martin Takac
Machine Learning Faculty Publications