Alexander V. Gasnikov

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 149

Top Venues

Publications

Saveliy Chezhegov, Yaroslav Klyukin, Andrei Semenov, Aleksandr Beznosikov, Alexander V. Gasnikov, Samuel Horváth, Martin Takác, Eduard Gorbunov
Gradient Clipping Improves AdaGrad when the Noise Is Heavy-Tailed. CoRR (2024)
Mikhail Rudakov, Aleksandr Beznosikov, Yaroslav Kholodov, Alexander V. Gasnikov
Activations and Gradients Compression for Model-Parallel Training. CoRR (2024)
Petr Ostroukhov, Aigerim Zhumabayeva, Chulu Xiang, Alexander V. Gasnikov, Martin Takác, Dmitry Kamzolov
AdaBatchGrad: Combining Adaptive Batch Size and Adaptive Step Size. CoRR (2024)
Meruza Kubentayeva, Demyan Yarmoshik, Michael Persiianov, Alexey Kroshnin, Ekaterina Kotliarova, Nazarii Tupitsa, Dmitry Pasechnyuk, Alexander V. Gasnikov, Vladimir Shvetsov, Leonid Baryshev, Alexey Shurupov
Primal-dual gradient methods for searching network equilibria in combined models with nested choice structure and capacity constraints. Comput. Manag. Sci. 21 (1) (2024)
Dmitry Metelev, Alexander Rogozin, Alexander V. Gasnikov, Dmitry Kovalev
Decentralized saddle-point problems with different constants of strong convexity and strong concavity. Comput. Manag. Sci. 21 (1) (2024)
Saveliy Chezhegov, Sergey Skorik, Nikolas Khachaturov, Danil Shalagin, Aram Avetisyan, Aleksandr Beznosikov, Martin Takác, Yaroslav Kholodov, Alexander V. Gasnikov
Local Methods with Adaptivity via Scaling. CoRR (2024)
Vitali Pirau, Aleksandr Beznosikov, Martin Takác, Vladislav Matyukhin, Alexander V. Gasnikov
Preconditioning meets biased compression for efficient distributed optimization. Comput. Manag. Sci. 21 (1) (2024)
Nikita Puchkin, Eduard Gorbunov, Nikolay Kutuzov, Alexander V. Gasnikov
Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems. AISTATS (2024)
Andrei Semenov, Vladimir Ivanov, Aleksandr Beznosikov, Alexander V. Gasnikov
Sparse Concept Bottleneck Models: Gumbel Tricks in Contrastive Learning. CoRR (2024)
Dmitry Kovalev, Ekaterina Borodich, Alexander V. Gasnikov, Dmitrii Feoktistov
Lower Bounds and Optimal Algorithms for Non-Smooth Convex Decentralized Optimization over Time-Varying Networks. CoRR (2024)
Nikita Kornilov, Alexander V. Gasnikov, Alexander Korotin
Optimal Flow Matching: Learning Straight Trajectories in Just One Step. CoRR (2024)
Demyan Yarmoshik, Alexander Rogozin, Alexander V. Gasnikov
Decentralized optimization with affine constraints over time-varying networks. Comput. Manag. Sci. 21 (1) (2024)
Dmitry Metelev, Aleksandr Beznosikov, Alexander Rogozin, Alexander V. Gasnikov, Anton V. Proskurnikov
Decentralized optimization over slowly time-varying graphs: algorithms and lower bounds. Comput. Manag. Sci. 21 (1) (2024)
Ruslan Nazykov, Aleksandr Shestakov, Vladimir Solodkin, Aleksandr Beznosikov, Gauthier Gidel, Alexander V. Gasnikov
Stochastic Frank-Wolfe: Unified Analysis and Zoo of Special Cases. AISTATS (2024)
Daniil Medyakov, Gleb Molodtsov, Aleksandr Beznosikov, Alexander V. Gasnikov
Optimal Data Splitting in Distributed Optimization for Machine Learning. CoRR (2024)
Yuriy Dorn, Nikita Kornilov, Nikolay Kutuzov, Alexander Nazin, Eduard Gorbunov, Alexander V. Gasnikov
Implicitly normalized forecaster with clipping for linear and non-linear heavy-tailed multi-armed bandits. Comput. Manag. Sci. 21 (1) (2024)
Olga Yufereva, Michael Persiianov, Pavel E. Dvurechensky, Alexander V. Gasnikov, Dmitry Kovalev
Decentralized convex optimization on time-varying networks with application to Wasserstein barycenters. Comput. Manag. Sci. 21 (1) (2024)
Artem Agafonov, Dmitry Kamzolov, Alexander V. Gasnikov, Ali Kavis, Kimon Antonakopoulos, Volkan Cevher, Martin Takác
Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness. ICLR (2024)
Artem Agafonov, Dmitry Kamzolov, Pavel E. Dvurechensky, Alexander V. Gasnikov, Martin Takác
Inexact tensor methods and their application to stochastic convex optimization. Optim. Methods Softw. 39 (1) (2024)
Dmitry Metelev, Alexander Rogozin, Dmitry Kovalev, Alexander V. Gasnikov
Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks? ICML (2023)
Aleksandr Beznosikov, Alexander V. Gasnikov
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities. CoRR (2023)
Aleksandr V. Lobanov, Andrew Veprikov, Georgiy Konin, Aleksandr Beznosikov, Alexander V. Gasnikov, Dmitry Kovalev
Non-smooth setting of stochastic decentralized convex optimization problem over time-varying Graphs. Comput. Manag. Sci. 20 (1) (2023)
Svetlana Tkachenko, Artem Andreev, Aleksandr Beznosikov, Alexander V. Gasnikov
Real Acceleration of Communication Process in Distributed Algorithms with Compression. OPTIMA (2023)
Aleksandr V. Lobanov, Alexander V. Gasnikov
Accelerated Zero-Order SGD Method for Solving the Black Box Optimization Problem Under "Overparametrization" Condition. OPTIMA (2023)
Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander V. Gasnikov, Alexey Naumov, Eric Moulines
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities. NeurIPS (2023)
Nikita Kornilov, Alexander V. Gasnikov, Pavel E. Dvurechensky, Darina Dvinskikh
Gradient-free methods for non-smooth convex stochastic optimization with heavy-tailed noise on convex compact. Comput. Manag. Sci. 20 (1) (2023)
Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander V. Gasnikov, Alexey Naumov, Eric Moulines
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities. CoRR (2023)
Yuriy Dorn, Kornilov Nikita, Nikolay Kutuzov, Alexander Nazin, Eduard Gorbunov, Alexander V. Gasnikov
Implicitly normalized forecaster with clipping for linear and non-linear heavy-tailed multi-armed bandits. CoRR (2023)
Dmitry Pasechnyuk, Michael Persiianov, Pavel E. Dvurechensky, Alexander V. Gasnikov
Algorithms for Euclidean-Regularised Optimal Transport. OPTIMA (2023)
Abdurakhmon Sadiev, Marina Danilova, Eduard Gorbunov, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik
High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance. ICML (2023)
Nikita Kornilov, Ohad Shamir, Aleksandr V. Lobanov, Darina Dvinskikh, Alexander V. Gasnikov, Innokentiy Shibaev, Eduard Gorbunov, Samuel Horváth
Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance. NeurIPS (2023)
N. A. Il'tyakov, M. A. Obozov, I. M. Dyshlevski, Demyan Yarmoshik, M. B. Kubentaeva, Alexander V. Gasnikov, Evgenia Gasnikova
On Accelerated Coordinate Descent Methods for Searching Equilibria in Two-Stage Transportation Equilibrium Traffic Flow Distribution Model. Program. Comput. Softw. 49 (6) (2023)
Egor Gladin, Maksim Lavrik-Karmazin, Karina Zainullina, Varvara Rudenko, Alexander V. Gasnikov, Martin Takác
Algorithm for Constrained Markov Decision Process with Linear Convergence. AISTATS (2023)
Aleksandr Beznosikov, Martin Takác, Alexander V. Gasnikov
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities. NeurIPS (2023)
Nikita Puchkin, Eduard Gorbunov, Nikolay Kutuzov, Alexander V. Gasnikov
Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems. CoRR (2023)
Eduard Gorbunov, Abdurakhmon Sadiev, Marina Danilova, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik
High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise. CoRR (2023)
Artem Vasin, Alexander V. Gasnikov, Pavel E. Dvurechensky, Vladimir G. Spokoiny
Accelerated gradient methods with absolute and relative noise in the gradient. Optim. Methods Softw. 38 (6) (2023)
R. A. Vedernikov, Alexander Rogozin, Alexander V. Gasnikov
Decentralized Conditional Gradient Method on Time-Varying Graphs. Program. Comput. Softw. 49 (6) (2023)
Sergey Guminov, Alexander V. Gasnikov, Ilya A. Kuruzov
Accelerated methods for weakly-quasi-convex optimization problems. Comput. Manag. Sci. 20 (1) (2023)
Abdurakhmon Sadiev, Marina Danilova, Eduard Gorbunov, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik
High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance. CoRR (2023)
Aleksandr Beznosikov, Alexander V. Gasnikov
Compression and Data Similarity: Combination of Two Techniques for Communication-Efficient Solving of Distributed Variational Inequalities. OPTIMA (2022)
Vasilii Novitskii, Alexander V. Gasnikov
Improved exploitation of higher order smoothness in derivative-free optimization. Optim. Lett. 16 (7) (2022)
Dmitry Kovalev, Alexander V. Gasnikov, Grigory Malinovsky
An Optimal Algorithm for Strongly Convex Min-min Optimization. CoRR (2022)
Ye Tian, Gesualdo Scutari, Tianyu Cao, Alexander V. Gasnikov
Acceleration in Distributed Optimization under Similarity. AISTATS (2022)
Aleksandr Beznosikov, Pavel E. Dvurechensky, Anastasia Koloskova, Valentin Samokhin, Sebastian U. Stich, Alexander V. Gasnikov
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities. NeurIPS (2022)
Dmitry Kovalev, Alexander V. Gasnikov
The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization. CoRR (2022)
Aleksandr Beznosikov, Peter Richtárik, Michael Diskin, Max Ryabinin, Alexander V. Gasnikov
Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees. NeurIPS (2022)
Dmitry Kovalev, Alexander V. Gasnikov
The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization. NeurIPS (2022)
Innokentiy Shibaev, Pavel E. Dvurechensky, Alexander V. Gasnikov
Zeroth-order methods for noisy Hölder-gradient functions. Optim. Lett. 16 (7) (2022)
Anton Anikin, Alexander V. Gasnikov, Alexander Gornov, Dmitry Kamzolov, Yury Maximov, Yurii E. Nesterov
Efficient numerical methods to solve sparse linear equations with application to PageRank. Optim. Methods Softw. 37 (3) (2022)
Aleksandr Beznosikov, Aibek Alanov, Dmitry Kovalev, Martin Takác, Alexander V. Gasnikov
On Scaled Methods for Saddle Point Problems. CoRR (2022)
Eduard Gorbunov, Marina Danilova, David Dobre, Pavel E. Dvurechenskii, Alexander V. Gasnikov, Gauthier Gidel
Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise. NeurIPS (2022)
Dmitry Kovalev, Aleksandr Beznosikov, Ekaterina Borodich, Alexander V. Gasnikov, Gesualdo Scutari
Optimal Gradient Sliding and its Application to Distributed Optimization Under Similarity. CoRR (2022)
Anastasiya Ivanova, Pavel E. Dvurechensky, Evgeniya A. Vorontsova, Dmitry Pasechnyuk, Alexander V. Gasnikov, Darina Dvinskikh, Alexander Tyurin
Oracle Complexity Separation in Convex Optimization. J. Optim. Theory Appl. 193 (1) (2022)
Daniil Tiapkin, Alexander V. Gasnikov
Primal-Dual Stochastic Mirror Descent for MDPs. AISTATS (2022)
Dmitry Kovalev, Aleksandr Beznosikov, Ekaterina Borodich, Alexander V. Gasnikov, Gesualdo Scutari
Optimal Gradient Sliding and its Application to Optimal Distributed Optimization Under Similarity. NeurIPS (2022)
Pavel E. Dvurechensky, Dmitry Kamzolov, Aleksandr Lukashevich, Soomin Lee, Erik Ordentlich, César A. Uribe, Alexander V. Gasnikov
Hyperfast second-order local solvers for efficient statistically preconditioned distributed optimization. EURO J. Comput. Optim. 10 (2022)
Slavomír Hanzely, Dmitry Kamzolov, Dmitry Pasechnyuk, Alexander V. Gasnikov, Peter Richtárik, Martin Takác
A Damped Newton Method Achieves Global $\mathcal O \left(\frac{1}{k^2}\right)$ and Local Quadratic Convergence Rate. NeurIPS (2022)
Aleksandr Beznosikov, Boris Polyak, Eduard Gorbunov, Dmitry Kovalev, Alexander V. Gasnikov
Smooth Monotone Stochastic Variational Inequalities and Saddle Point Problems - Survey. CoRR (2022)
Alexander Rogozin, Demyan Yarmoshik, Ksenia Kopylova, Alexander V. Gasnikov
Decentralized Strongly-Convex Optimization with Affine Constraints: Primal and Dual Approaches. OPTIMA (2) (2022)
Dmitry Kovalev, Alexander V. Gasnikov
The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization. CoRR (2022)
Dmitry Kovalev, Alexander V. Gasnikov, Peter Richtárik
Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling. NeurIPS (2022)
Eduard Gorbunov, Pavel E. Dvurechensky, Alexander V. Gasnikov
An Accelerated Method for Derivative-Free Smooth Stochastic Convex Optimization. SIAM J. Optim. 32 (2) (2022)
Aleksandr Beznosikov, Alexander V. Gasnikov
SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities. CoRR (2022)
Eduard Gorbunov, Marina Danilova, David Dobre, Pavel E. Dvurechensky, Alexander V. Gasnikov, Gauthier Gidel
Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise. CoRR (2022)
Daniil Tiapkin, Alexander V. Gasnikov, Pavel E. Dvurechensky
Stochastic saddle-point optimization for the Wasserstein barycenter problem. Optim. Lett. 16 (7) (2022)
Dmitry Kovalev, Aleksandr Beznosikov, Abdurakhmon Sadiev, Michael Persiianov, Peter Richtárik, Alexander V. Gasnikov
Optimal Algorithms for Decentralized Stochastic Variational Inequalities. NeurIPS (2022)
Abdurakhmon Sadiev, Ekaterina Borodich, Aleksandr Beznosikov, Darina Dvinskikh, Saveliy Chezhegov, Rachael Tappenden, Martin Takác, Alexander V. Gasnikov
Decentralized personalized federated learning: Lower bounds and optimal algorithm for all personalization modes. EURO J. Comput. Optim. 10 (2022)
Aleksandr Beznosikov, Alexander V. Gasnikov
Compression and Data Similarity: Combination of Two Techniques for Communication-Efficient Solving of Distributed Variational Inequalities. CoRR (2022)
Alexander V. Gasnikov, Anton Novitskii, Vasilii Novitskii, Farshed Abdukhakimov, Dmitry Kamzolov, Aleksandr Beznosikov, Martin Takác, Pavel E. Dvurechensky, Bin Gu
The power of first-order smooth optimization for black-box non-smooth problems. ICML (2022)
Egor Gladin, Maksim Lavrik-Karmazin, Karina Zainullina, Varvara Rudenko, Alexander V. Gasnikov, Martin Takác
Algorithm for Constrained Markov Decision Process with Linear Convergence. CoRR (2022)
Dmitry Kovalev, Aleksandr Beznosikov, Abdurakhmon Sadiev, Michael Persiianov, Peter Richtárik, Alexander V. Gasnikov
Optimal Algorithms for Decentralized Stochastic Variational Inequalities. CoRR (2022)
Ekaterina Borodich, Vladislav Tominin, Yaroslav Tominin, Dmitry Kovalev, Alexander V. Gasnikov, Pavel E. Dvurechensky
Accelerated variance-reduced methods for saddle-point problems. EURO J. Comput. Optim. 10 (2022)
Dmitry Kovalev, Alexander V. Gasnikov
The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization. NeurIPS (2022)
Fedor S. Stonyakin, Alexander V. Gasnikov, Pavel E. Dvurechensky, Alexander A. Titov, Mohammad S. Alkousa
Generalized Mirror Prox Algorithm for Monotone Variational Inequalities: Universality and Inexact Oracle. J. Optim. Theory Appl. 194 (3) (2022)
Ye Tian, Gesualdo Scutari, Tianyu Cao, Alexander V. Gasnikov
Acceleration in Distributed Optimization Under Similarity. CoRR (2021)
Aleksandr Beznosikov, Vadim Sushko, Abdurakhmon Sadiev, Alexander V. Gasnikov
Decentralized Personalized Federated Min-Max Problems. CoRR (2021)
Amir Daneshmand, Gesualdo Scutari, Pavel E. Dvurechensky, Alexander V. Gasnikov
Newton Method over Networks is Fast up to the Statistical Precision. ICML (2021)
Alexander Rogozin, Vladislav Lukoshkin, Alexander V. Gasnikov, Dmitry Kovalev, Egor Shulgin
Towards Accelerated Rates for Distributed Optimization over Time-Varying Networks. OPTIMA (2021)
Vladislav Matyukhin, Sergey Igorevich Kabanikhin, Maxim A. Shishlenin, Nikita S. Novikov, Artem Vasin, Alexander V. Gasnikov
Convex Optimization with Inexact Gradients in Hilbert Space and Applications to Elliptic Inverse Problems. MOTOR (2021)
Alexander Rogozin, Mikhail Bochko, Pavel E. Dvurechensky, Alexander V. Gasnikov, Vladislav Lukoshkin
An Accelerated Method For Decentralized Distributed Stochastic Optimization Over Time-Varying Graphs. CDC (2021)
Aleksandr Beznosikov, Pavel E. Dvurechensky, Anastasia Koloskova, Valentin Samokhin, Sebastian U. Stich, Alexander V. Gasnikov
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities. CoRR (2021)
Aleksandr Beznosikov, Gesualdo Scutari, Alexander Rogozin, Alexander V. Gasnikov
Distributed Saddle-Point Problems Under Data Similarity. NeurIPS (2021)
Aleksandr Beznosikov, Gesualdo Scutari, Alexander Rogozin, Alexander V. Gasnikov
Distributed Saddle-Point Problems Under Similarity. CoRR (2021)
Artem Agafonov, Pavel E. Dvurechensky, Gesualdo Scutari, Alexander V. Gasnikov, Dmitry Kamzolov, Aleksandr Lukashevich, Amir Daneshmand
An Accelerated Second-Order Method for Distributed Stochastic Optimization. CDC (2021)
Egor Gladin, Mohammad S. Alkousa, Alexander V. Gasnikov
Solving Convex Min-Min Problems with Smoothness and Strong Convexity in One Group of Variables and Low Dimension in the Other. Autom. Remote. Control. 82 (10) (2021)
Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Alexander Rogozin, Alexander V. Gasnikov
ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks. CoRR (2021)
Dmitry Kovalev, Elnur Gasanov, Peter Richtárik, Alexander V. Gasnikov
Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks. CoRR (2021)
Dmitry Kovalev, Alexander V. Gasnikov, Peter Richtárik
Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling. CoRR (2021)
Yurii E. Nesterov, Alexander V. Gasnikov, Sergey Guminov, Pavel E. Dvurechensky
Primal-dual accelerated gradient methods with small-dimensional relaxation oracle. Optim. Methods Softw. 36 (4) (2021)
Dmitry Kamzolov, Pavel E. Dvurechensky, Alexander V. Gasnikov
Universal intermediate gradient method for convex problems with inexact oracle. Optim. Methods Softw. 36 (6) (2021)
Sergey Guminov, Pavel E. Dvurechensky, Nazarii Tupitsa, Alexander V. Gasnikov
On a Combination of Alternating Minimization and Nesterov's Momentum. ICML (2021)
César A. Uribe, Soomin Lee, Alexander V. Gasnikov, Angelia Nedic
A dual approach for optimal algorithms in distributed optimization over networks. Optim. Methods Softw. 36 (1) (2021)
Alexander Rogozin, Aleksandr Beznosikov, Darina Dvinskikh, Dmitry Kovalev, Pavel E. Dvurechensky, Alexander V. Gasnikov
Decentralized Distributed Optimization for Saddle Point Problems. CoRR (2021)
Ivan Stepanov, Artyom Voronov, Aleksandr Beznosikov, Alexander V. Gasnikov
One-Point Gradient-Free Methods for Composite Optimization with Applications to Distributed Optimization. CoRR (2021)
Eduard A. Gorbunov, Marina Danilova, Innokentiy Shibaev, Pavel E. Dvurechensky, Alexander V. Gasnikov
Near-Optimal High Probability Complexity Bounds for Non-Smooth Stochastic Optimization with Heavy-Tailed Noise. CoRR (2021)
Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Alexander Rogozin, Alexander V. Gasnikov
ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks. ICML (2021)
Pavel E. Dvurechensky, Eduard A. Gorbunov, Alexander V. Gasnikov
An accelerated directional derivative method for smooth stochastic convex optimization. Eur. J. Oper. Res. 290 (2) (2021)
Aleksandr Beznosikov, Vasilii Novitskii, Alexander V. Gasnikov
One-Point Gradient-Free Methods for Smooth and Non-smooth Saddle-Point Problems. MOTOR (2021)
Aleksandr Beznosikov, Peter Richtárik, Michael Diskin, Max Ryabinin, Alexander V. Gasnikov
Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees. CoRR (2021)

Alexander V. Gasnikov.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Alexander V. Gasnikov