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Artem Agafonov
Artem Agafonov
Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)
Verified email at mbzuai.ac.ae
Title
Cited by
Cited by
Year
Gradient methods for problems with inexact model of the objective
FS Stonyakin, D Dvinskikh, P Dvurechensky, A Kroshnin, O Kuznetsova, ...
Mathematical Optimization Theory and Operations Research: 18th International …, 2019
572019
Inexact model: a framework for optimization and variational inequalities
F Stonyakin, A Tyurin, A Gasnikov, P Dvurechensky, A Agafonov, ...
Optimization Methods and Software 36 (6), 1155-1201, 2021
452021
Inexact relative smoothness and strong convexity for optimization and variational inequalities by inexact model
F Stonyakin, A Tyurin, A Gasnikov, P Dvurechensky, A Agafonov, ...
arXiv preprint arXiv:2001.09013, 2020
202020
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
182021
Inexact model: A framework for optimization and variational inequalities
F Stonyakin, A Gasnikov, A Tyurin, D Pasechnyuk, A Agafonov, ...
arXiv preprint arXiv:1902.00990, 2019
162019
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
142023
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
102022
Accelerated adaptive cubic regularized quasi-newton methods
D Kamzolov, K Ziu, A Agafonov, M Takác
arXiv preprint arXiv:2302.04987, 2, 2023
52023
Exploiting higher-order derivatives in convex optimization methods
D Kamzolov, A Gasnikov, P Dvurechensky, A Agafonov, M Takáč
arXiv preprint arXiv:2208.13190, 2022
52022
Flecs-cgd: A federated learning second-order framework via compression and sketching with compressed gradient differences
A Agafonov, B Erraji, M Takáč
arXiv preprint arXiv:2210.09626, 2022
32022
In Quest of Ground Truth: Learning Confident Models and Estimating Uncertainty in the Presence of Annotator Noise
AA Hashmi
32022
Advancing the lower bounds: An accelerated, stochastic, second-order method with optimal adaptation to inexactness
A Agafonov, D Kamzolov, A Gasnikov, K Antonakopoulos, V Cevher, ...
arXiv preprint arXiv:2309.01570, 2023
22023
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
12023
Lower bounds for conditional gradient type methods for minimizing smooth strongly convex functions
A Agafonov
arXiv preprint arXiv:2003.07073, 2020
12020
Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations
A Agafonov, P Ostroukhov, K Yakovlev, E Gorbunov, M Takáč, A Gasnikov, ...
arXiv preprint arXiv:2405.15990, 2024
2024
Нижние оценки для методов типа условного градиента для задач минимизации гладких сильно выпуклых функций
АД Агафонов
Компьютерные исследования и моделирование 14 (2), 213-223, 2022
2022
Градиентные методы для задач оптимизации, допускающие существование неточной сильно выпуклой модели целевой функции
АД Агафонов, ФС Стонякин
Труды Московского физико-технического института 11 (3 (43)), 4-19, 2019
2019
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