Dmitry Kamzolov
Dmitry Kamzolov
Research Associate, Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)
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Cited by
Cited by
Recent theoretical advances in non-convex optimization
M Danilova, P Dvurechensky, A Gasnikov, E Gorbunov, S Guminov, ...
High-Dimensional Optimization and Probability: With a View Towards Data …, 2022
Universal intermediate gradient method for convex problems with inexact oracle
D Kamzolov, P Dvurechensky, AV Gasnikov
Optimization Methods and Software 36 (6), 1289-1316, 2021
The power of first-order smooth optimization for black-box non-smooth problems
A Gasnikov, A Novitskii, V Novitskii, F Abdukhakimov, D Kamzolov, ...
Proceedings of the 39th International Conference on Machine Learning 162 …, 2022
Accelerated meta-algorithm for convex optimization problems
AV Gasnikov, DM Dvinskikh, PE Dvurechensky, DI Kamzolov, ...
Computational Mathematics and Mathematical Physics 61, 17-28, 2021
Efficient numerical methods to solve sparse linear equations with application to pagerank
A Anikin, A Gasnikov, A Gornov, D Kamzolov, Y Maximov, Y Nesterov
Optimization Methods and Software 37 (3), 907-935, 2022
Universal method with inexact oracle and its applications for searching equillibriums in multistage transport problems
A Gasnikov, P Dvurechensky, D Kamzolov, Y Nesterov, V Spokoiny, ...
arXiv preprint arXiv:1506.00292, 2015
Near-optimal hyperfast second-order method for convex optimization and its sliding
D Kamzolov, A Gasnikov
arXiv preprint arXiv:2002.09050, 2020
Optimal combination of tensor optimization methods
D Kamzolov, A Gasnikov, P Dvurechensky
International Conference on Optimization and Applications, 166-183, 2020
An accelerated second-order method for distributed stochastic optimization
A Agafonov, P Dvurechensky, G Scutari, A Gasnikov, D Kamzolov, ...
2021 60th IEEE Conference on Decision and Control (CDC), 2407-2413, 2021
A Damped Newton Method Achieves Global and Local Quadratic Convergence Rate
S Hanzely, D Kamzolov, D Pasechnyuk, A Gasnikov, P Richtárik, M Takáč
Advances in Neural Information Processing Systems, 2022
Hyperfast second-order local solvers for efficient statistically preconditioned distributed optimization
P Dvurechensky, D Kamzolov, A Lukashevich, S Lee, E Ordentlich, ...
EURO Journal on Computational Optimization 10, 100045, 2022
Composite optimization for the resource allocation problem
A Ivanova, P Dvurechensky, A Gasnikov, D Kamzolov
Optimization Methods and Software 36 (4), 720-754, 2021
Inexact tensor methods and their application to stochastic convex optimization
A Agafonov, D Kamzolov, P Dvurechensky, A Gasnikov, M Takáč
Optimization Methods and Software, 1-42, 2023
Suppressing poisoning attacks on federated learning for medical imaging
N Alkhunaizi, D Kamzolov, M Takáč, K Nandakumar
International Conference on Medical Image Computing and Computer-Assisted …, 2022
Flecs: A federated learning second-order framework via compression and sketching
A Agafonov, D Kamzolov, R Tappenden, A Gasnikov, M Takáč
arXiv preprint arXiv:2206.02009, 2022
Gradient and gradient-free methods for stochastic convex optimization with inexact oracle
A Gasnikov, P Dvurechensky, D Kamzolov
arXiv preprint arXiv:1502.06259, 2015
Stochastic Gradient Descent with Preconditioned Polyak Step-size
F Abdukhakimov, C Xiang, D Kamzolov, M Takáč
arXiv preprint arXiv:2310.02093, 2023
Cubic Regularization is the Key! The First Accelerated Quasi-Newton Method with a Global Convergence Rate of for Convex Functions
D Kamzolov, K Ziu, A Agafonov, M Takáč
arXiv preprint arXiv:2302.04987, 2023
Stochastic gradient methods with preconditioned updates
A Sadiev, A Beznosikov, AJ Almansoori, D Kamzolov, R Tappenden, ...
Journal of Optimization Theory and Applications 201 (2), 471-489, 2024
Exploiting higher-order derivatives in convex optimization methods
D Kamzolov, A Gasnikov, P Dvurechensky, A Agafonov, M Takáč
arXiv preprint arXiv:2208.13190, 2022
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