Alexander V. Gasnikov
Orcid: 0000-0002-7386-039XAffiliations:
- Moscow Institute of Physics and Technology, Russia
- Russian Academy of Sciences, Kharkevich Institute for Information Transmission Problems, Moscow, Russia
According to our database1,
Alexander V. Gasnikov
authored at least 121 papers
between 2012 and 2024.
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Bibliography
2024
Decentralized convex optimization on time-varying networks with application to Wasserstein barycenters.
Comput. Manag. Sci., June, 2024
Comput. Manag. Sci., June, 2024
Comput. Manag. Sci., June, 2024
Decentralized saddle-point problems with different constants of strong convexity and strong concavity.
Comput. Manag. Sci., June, 2024
Decentralized optimization over slowly time-varying graphs: algorithms and lower bounds.
Comput. Manag. Sci., June, 2024
Primal-dual gradient methods for searching network equilibria in combined models with nested choice structure and capacity constraints.
Comput. Manag. Sci., June, 2024
Implicitly normalized forecaster with clipping for linear and non-linear heavy-tailed multi-armed bandits.
Comput. Manag. Sci., June, 2024
2023
Program. Comput. Softw., December, 2023
On Accelerated Coordinate Descent Methods for Searching Equilibria in Two-Stage Transportation Equilibrium Traffic Flow Distribution Model.
Program. Comput. Softw., December, 2023
Non-smooth setting of stochastic decentralized convex optimization problem over time-varying Graphs.
Comput. Manag. Sci., December, 2023
Gradient-free methods for non-smooth convex stochastic optimization with heavy-tailed noise on convex compact.
Comput. Manag. Sci., December, 2023
Comput. Manag. Sci., December, 2023
Optim. Methods Softw., November, 2023
CoRR, 2023
High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise.
CoRR, 2023
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities.
CoRR, 2023
Real Acceleration of Communication Process in Distributed Algorithms with Compression.
Proceedings of the Optimization and Applications - 14th International Conference, 2023
Proceedings of the Optimization and Applications - 14th International Conference, 2023
Accelerated Zero-Order SGD Method for Solving the Black Box Optimization Problem Under "Overparametrization" Condition.
Proceedings of the Optimization and Applications - 14th International Conference, 2023
Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance.
Proceedings of the International Conference on Machine Learning, 2023
Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks?
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
SIAM J. Optim., 2022
Efficient numerical methods to solve sparse linear equations with application to PageRank.
Optim. Methods Softw., 2022
Optim. Lett., 2022
Optim. Lett., 2022
Generalized Mirror Prox Algorithm for Monotone Variational Inequalities: Universality and Inexact Oracle.
J. Optim. Theory Appl., 2022
Decentralized personalized federated learning: Lower bounds and optimal algorithm for all personalization modes.
EURO J. Comput. Optim., 2022
Hyperfast second-order local solvers for efficient statistically preconditioned distributed optimization.
EURO J. Comput. Optim., 2022
EURO J. Comput. Optim., 2022
SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities.
CoRR, 2022
Smooth Monotone Stochastic Variational Inequalities and Saddle Point Problems - Survey.
CoRR, 2022
Optimal Gradient Sliding and its Application to Distributed Optimization Under Similarity.
CoRR, 2022
Decentralized Strongly-Convex Optimization with Affine Constraints: Primal and Dual Approaches.
Proceedings of the Advances in Optimization and Applications, 2022
Proceedings of the Advances in Optimization and Applications, 2022
Compression and Data Similarity: Combination of Two Techniques for Communication-Efficient Solving of Distributed Variational Inequalities.
Proceedings of the Optimization and Applications - 13th International Conference, 2022
Some Adaptive First-Order Methods for Variational Inequalities with Relatively Strongly Monotone Operators and Generalized Smoothness.
Proceedings of the Optimization and Applications - 13th International Conference, 2022
Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Optimal Gradient Sliding and its Application to Optimal Distributed Optimization Under Similarity.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
A Damped Newton Method Achieves Global $\mathcal O \left(\frac{1}{k^2}\right)$ and Local Quadratic Convergence Rate.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
Optim. Methods Softw., 2021
Optim. Methods Softw., 2021
Optim. Methods Softw., 2021
Optim. Methods Softw., 2021
Optim. Methods Softw., 2021
An accelerated directional derivative method for smooth stochastic convex optimization.
Eur. J. Oper. Res., 2021
One-Point Gradient-Free Methods for Composite Optimization with Applications to Distributed Optimization.
CoRR, 2021
Near-Optimal High Probability Complexity Bounds for Non-Smooth Stochastic Optimization with Heavy-Tailed Noise.
CoRR, 2021
Solving Convex Min-Min Problems with Smoothness and Strong Convexity in One Group of Variables and Low Dimension in the Other.
Autom. Remote. Control., 2021
Proceedings of the Optimization and Applications - 12th International Conference, 2021
Proceedings of the Optimization and Applications - 12th International Conference, 2021
Near-Optimal Decentralized Algorithms for Saddle Point Problems over Time-Varying Networks.
Proceedings of the Optimization and Applications - 12th International Conference, 2021
Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Convex Optimization with Inexact Gradients in Hilbert Space and Applications to Elliptic Inverse Problems.
Proceedings of the Mathematical Optimization Theory and Operations Research, 2021
Proceedings of the Mathematical Optimization Theory and Operations Research, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
An Accelerated Method For Decentralized Distributed Stochastic Optimization Over Time-Varying Graphs.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021
2020
IEEE Trans. Control. Netw. Syst., 2020
Proceedings of the Optimization and Applications - 11th International Conference, 2020
Proceedings of the Optimization and Applications - 11th International Conference, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Mathematical Optimization Theory and Operations Research, 2020
Proceedings of the 59th IEEE Conference on Decision and Control, 2020
2019
Accelerated Gradient-Free Optimization Methods with a Non-Euclidean Proximal Operator.
Autom. Remote. Control., 2019
Autom. Remote. Control., 2019
Proceedings of the Mathematical Optimization Theory and Operations Research, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the Conference on Learning Theory, 2019
Near Optimal Methods for Minimizing Convex Functions with Lipschitz $p$-th Derivatives.
Proceedings of the Conference on Learning Theory, 2019
On Primal and Dual Approaches for Distributed Stochastic Convex Optimization over Networks.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019
2018
Gradient-Free Two-Point Methods for Solving Stochastic Nonsmooth Convex Optimization Problems with Small Non-Random Noises.
Autom. Remote. Control., 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn's Algorithm.
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 57th IEEE Conference on Decision and Control, 2018
2017
CoRR, 2017
Randomized Similar Triangles Method: A Unifying Framework for Accelerated Randomized Optimization Methods (Coordinate Descent, Directional Search, Derivative-Free Method).
CoRR, 2017
Stochastic online optimization. Single-point and multi-point non-linear multi-armed bandits. Convex and strongly-convex case.
Autom. Remote. Control., 2017
2016
Stochastic Intermediate Gradient Method for Convex Problems with Stochastic Inexact Oracle.
J. Optim. Theory Appl., 2016
Gradient-free proximal methods with inexact oracle for convex stochastic nonsmooth optimization problems on the simplex.
Autom. Remote. Control., 2016
Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Primal-Dual Method for Searching Equilibrium in Hierarchical Congestion Population Games.
Proceedings of the Supplementary Proceedings of the 9th International Conference on Discrete Optimization and Operations Research and Scientific School (DOOR 2016), Vladivostok, Russia, September 19, 2016
Fast Primal-Dual Gradient Method for Strongly Convex Minimization Problems with Linear Constraints.
Proceedings of the Discrete Optimization and Operations Research, 2016
2014
2012