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

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

Suppressing Poisoning Attacks on Federated Learning for Medical Imaging, Naif Alkhunaizi, Dmitry Kamzolov, Martin Takac, Karthik Nandakumar
Martin Takac

Suppressing Poisoning Attacks on Federated Learning for Medical Imaging, Naif Alkhunaizi, Dmitry Kamzolov, Martin Takac, Karthik Nandakumar
Karthik Nandakumar

Suppressing Poisoning Attacks on Federated Learning for Medical Imaging, Naif Alkhunaizi, Dmitry Kamzolov, Martin Takac, Karthik Nandakumar
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

Stochastic Gradient Methods with Preconditioned Updates, Abdurakhmon Sadiev, Aleksandr Beznosikov, Abdulla Jasem Almansoori, Dmitry Kamzolov, Rachael Tappenden, 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

Stochastic Gradient Methods with Preconditioned Updates, Abdurakhmon Sadiev, Aleksandr Beznosikov, Abdulla Jasem Almansoori, Dmitry Kamzolov, Rachael Tappenden, 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

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

The Power Of First-Order Smooth Optimization for Black-Box Non-Smooth Problems, Alexander V. Gasnikov., Anton Novitskii, Vasilii Novitskii, Farshed Abdukhakimov, Dmitry Kamzolov, Aleksandr Beznosikov, Martin Takáč, Pavel Dvurechensky, Bin Gu
Bin Gu

The Power Of First-Order Smooth Optimization for Black-Box Non-Smooth Problems, Alexander V. Gasnikov., Anton Novitskii, Vasilii Novitskii, Farshed Abdukhakimov, Dmitry Kamzolov, Aleksandr Beznosikov, Martin Takáč, Pavel Dvurechensky, Bin Gu
Martin Takac

The Power Of First-Order Smooth Optimization for Black-Box Non-Smooth Problems, Alexander V. Gasnikov., Anton Novitskii, Vasilii Novitskii, Farshed Abdukhakimov, Dmitry Kamzolov, Aleksandr Beznosikov, Martin Takáč, Pavel Dvurechensky, Bin Gu
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