Optimal Combination of Tensor Optimization Methods. - Dmitry Kamzolov; Alexander V. Gasnikov; Pavel E. Dvurechensky (OPTIMA, 2020)

Recent Theoretical Advances in Non-Convex Optimization. - Marina Danilova; Pavel E. Dvurechensky; Alexander V. Gasnikov; Eduard Gorbunov; Sergey Guminov; Dmitry Kamzolov; Innokentiy Shibaev (CoRR, 2020)

An Accelerated Second-Order Method for Distributed Stochastic Optimization. - Artem Agafonov; Pavel E. Dvurechensky; Gesualdo Scutari; Alexander V. Gasnikov; Dmitry Kamzolov; Aleksandr Lukashevich; Amir Daneshmand (CDC, 2021)

Composite optimization for the resource allocation problem. - Anastasiya Ivanova; Pavel E. Dvurechensky; Alexander V. Gasnikov; Dmitry Kamzolov (Optim. Methods Softw., 2021)

Universal intermediate gradient method for convex problems with inexact oracle. - Dmitry Kamzolov; Pavel E. Dvurechensky; Alexander V. Gasnikov (Optim. Methods Softw., 2021)

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 Takác 001; Pavel E. Dvurechensky; Bin Gu 001 (ICML, 2022)

Suppressing Poisoning Attacks on Federated Learning for Medical Imaging. - Naif Alkhunaizi; Dmitry Kamzolov; Martin Takác 001; Karthik Nandakumar (MICCAI (8), 2022)

A Damped Newton Method Achieves Global $ mathcal O left( frac{1}{k^2} right)$ and Local Quadratic Convergence Rate. - Slavomír Hanzely; Dmitry Kamzolov; Dmitry Pasechnyuk; Alexander V. Gasnikov; Peter Richtárik; Martin Takác 001 (NeurIPS, 2022)

Hyperfast second-order local solvers for efficient statistically preconditioned distributed optimization. - Pavel E. Dvurechensky; Dmitry Kamzolov; Aleksandr Lukashevich; Soomin Lee; Erik Ordentlich; César A. Uribe; Alexander V. Gasnikov (EURO J. Comput. Optim., 2022)

Efficient numerical methods to solve sparse linear equations with application to PageRank. - Anton Anikin 002; Alexander V. Gasnikov; Alexander Gornov; Dmitry Kamzolov; Yury Maximov; Yurii E. Nesterov (Optim. Methods Softw., 2022)

Stochastic Gradient Descent with Preconditioned Polyak Step-size. - Farshed Abdukhakimov; Chulu Xiang; Dmitry Kamzolov; Martin Takác 001 (CoRR, 2023)

SANIA: Polyak-type Optimization Framework Leads to Scale Invariant Stochastic Algorithms. - Farshed Abdukhakimov; Chulu Xiang; Dmitry Kamzolov; Robert M. Gower; Martin Takác 001 (CoRR, 2023)

Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness. - Artem Agafonov; Dmitry Kamzolov; Alexander V. Gasnikov; Ali Kavis; Kimon Antonakopoulos; Volkan Cevher; Martin Takác 001 (ICLR, 2024)

Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations. - Artem Agafonov; Petr Ostroukhov; Roman Mozhaev; Konstantin Yakovlev; Eduard Gorbunov; Martin Takác 001; Alexander V. Gasnikov; Dmitry Kamzolov (NeurIPS, 2024)

AdaBatchGrad: Combining Adaptive Batch Size and Adaptive Step Size. - Petr Ostroukhov; Aigerim Zhumabayeva; Chulu Xiang; Alexander V. Gasnikov; Martin Takác 001; Dmitry Kamzolov (CoRR, 2024)

ψDAG: Projected Stochastic Approximation Iteration for DAG Structure Learning. - Klea Ziu; Slavomír Hanzely; Loka Li; Kun Zhang 001; Martin Takác 001; Dmitry Kamzolov (CoRR, 2024)

Inexact tensor methods and their application to stochastic convex optimization. - Artem Agafonov; Dmitry Kamzolov; Pavel E. Dvurechensky; Alexander V. Gasnikov; Martin Takác 001 (Optim. Methods Softw., 2024)

Stochastic Gradient Methods with Preconditioned Updates. - Abdurakhmon Sadiev; Aleksandr Beznosikov; Abdulla Jasem Almansoori; Dmitry Kamzolov; Rachael Tappenden; Martin Takác 001 (J. Optim. Theory Appl., 2024)

OPTAMI: Global Superlinear Convergence of High-order Methods. - Dmitry Kamzolov; Artem Agafonov; Dmitry Pasechnyuk; Alexander V. Gasnikov; Martin Takác 001 (ICLR, 2025)