Gradient Methods for Problems with Inexact Model of the Objective. - Fedor S. Stonyakin; Darina Dvinskikh; Pavel E. Dvurechensky; Alexey Kroshnin; Olesya Kuznetsova; Artem Agafonov; Alexander V. Gasnikov; Alexander Tyurin; César A. Uribe; Dmitry Pasechnyuk; Sergei Artamonov (MOTOR, 2019)

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)

Inexact model: a framework for optimization and variational inequalities. - Fedor S. Stonyakin; Alexander Tyurin; Alexander V. Gasnikov; Pavel E. Dvurechensky; Artem Agafonov; Darina Dvinskikh; Mohammad S. Alkousa; Dmitry Pasechnyuk; Sergei Artamonov; Victoria V. Piskunova (Optim. Methods Softw., 2021)

FLECS-CGD: A Federated Learning Second-Order Framework via Compression and Sketching with Compressed Gradient Differences. - Artem Agafonov; Brahim Erraji; Martin Takác 001 (CoRR, 2022)

In Quest of Ground Truth: Learning Confident Models and Estimating Uncertainty in the Presence of Annotator Noise. - Asma Ahmed Hashmi; Artem Agafonov; Aigerim Zhumabayeva; Mohammad Yaqub; 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)

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)

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

Learning Confident Classifiers in the Presence of Label Noise. - Asma Ahmed Hashmi; Aigerim Zhumabayeva; Nikita Kotelevskii; Artem Agafonov; Mohammad Yaqub; Maxim Panov; Martin Takác 001 (SDM, 2025)

Multi-Agent Path Finding For Large Agents Is Intractable. - Artem Agafonov; Konstantin Yakovlev (CoRR, 2025)