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Aleksandr Beznosikov
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2020 – today
- 2024
- [j7]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): 8 (2024) - [j6]Vitali Pirau, Aleksandr Beznosikov, Martin Takác, Vladislav Matyukhin, Alexander V. Gasnikov:
Preconditioning meets biased compression for efficient distributed optimization. Comput. Manag. Sci. 21(1): 14 (2024) - [j5]Abdurakhmon Sadiev, Aleksandr Beznosikov
Stochastic Gradient Methods with Preconditioned Updates. J. Optim. Theory Appl. 201(2): 471-489 (2024) - [j4]Aleksandr Beznosikov
Random-reshuffled SARAH does not need full gradient computations. Optim. Lett. 18(3): 727-749 (2024) - [c16]Ruslan Nazykov, Aleksandr Shestakov
Stochastic Frank-Wolfe: Unified Analysis and Zoo of Special Cases. AISTATS 2024: 4870-4878 - [c15]Aleksei Ustimenko, Aleksandr Beznosikov:
Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting. ICLR 2024 - [c14]Aleksandr Beznosikov, David Dobre, Gauthier Gidel:
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features. ICML 2024 - [i29]Mikhail Rudakov, Aleksandr Beznosikov, Yaroslav Kholodov, Alexander V. Gasnikov:
Activations and Gradients Compression for Model-Parallel Training. CoRR abs/2401.07788 (2024) - [i28]Daniil Medyakov, Gleb Molodtsov, Aleksandr Beznosikov, Alexander V. Gasnikov:
Optimal Data Splitting in Distributed Optimization for Machine Learning. CoRR abs/2401.07809 (2024) - [i27]Andrei Semenov
Sparse Concept Bottleneck Models: Gumbel Tricks in Contrastive Learning. CoRR abs/2404.03323 (2024) - [i26]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 abs/2406.00846 (2024) - [i25]Saveliy Chezhegov, Yaroslav Klyukin, Andrei Semenov
Gradient Clipping Improves AdaGrad when the Noise Is Heavy-Tailed. CoRR abs/2406.04443 (2024) - [i24]Dmitry Bylinkin, Kirill Degtyarev, Aleksandr Beznosikov:
Accelerated Stochastic ExtraGradient: Mixing Hessian and Gradient Similarity to Reduce Communication in Distributed and Federated Learning. CoRR abs/2409.14280 (2024) - 2023
- [j3]Aleksandr V. Lobanov, Andrew Veprikov
Non-smooth setting of stochastic decentralized convex optimization problem over time-varying Graphs. Comput. Manag. Sci. 20(1): 48 (2023) - [j2]Aleksandr Beznosikov, Samuel Horváth, Peter Richtárik, Mher Safaryan:
On Biased Compression for Distributed Learning. J. Mach. Learn. Res. 24: 276:1-276:50 (2023) - [c13]Aleksandr Beznosikov, Eduard Gorbunov, Hugo Berard, Nicolas Loizou:
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods. AISTATS 2023: 172-235 - [c12]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 - [c11]Aleksandr Beznosikov, Martin Takác, Alexander V. Gasnikov:
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities. NeurIPS 2023 - [c10]Svetlana Tkachenko, Artem Andreev, Aleksandr Beznosikov, Alexander V. Gasnikov:
Real Acceleration of Communication Process in Distributed Algorithms with Compression. OPTIMA 2023: 99-109 - [i23]Aleksandr Beznosikov, Alexander V. Gasnikov:
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities. CoRR abs/2302.07615 (2023) - [i22]Aleksandr Beznosikov, David Dobre, Gauthier Gidel:
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features. CoRR abs/2304.11737 (2023) - [i21]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 abs/2305.15938 (2023) - [i20]Aleksei Ustimenko, Aleksandr Beznosikov:
Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting. CoRR abs/2310.06081 (2023) - 2022
- [j1]Abdurakhmon Sadiev, Ekaterina Borodich, Aleksandr Beznosikov, Darina Dvinskikh
Decentralized personalized federated learning: Lower bounds and optimal algorithm for all personalization modes. EURO J. Comput. Optim. 10: 100041 (2022) - [c9]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: 7241-7265 - [c8]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 - [c7]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 - [c6]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 - [c5]Dmitry Kovalev, Aleksandr Beznosikov, Abdurakhmon Sadiev, Michael Persiianov, Peter Richtárik, Alexander V. Gasnikov:
Optimal Algorithms for Decentralized Stochastic Variational Inequalities. NeurIPS 2022 - [c4]Aleksandr Beznosikov, Alexander V. Gasnikov:
Compression and Data Similarity: Combination of Two Techniques for Communication-Efficient Solving of Distributed Variational Inequalities. OPTIMA 2022: 151-162 - [i19]Dmitry Kovalev
Optimal Algorithms for Decentralized Stochastic Variational Inequalities. CoRR abs/2202.02771 (2022) - [i18]Aleksandr Beznosikov, Eduard Gorbunov, Hugo Berard, Nicolas Loizou:
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods. CoRR abs/2202.07262 (2022) - [i17]Dmitry Kovalev, Aleksandr Beznosikov
Optimal Gradient Sliding and its Application to Distributed Optimization Under Similarity. CoRR abs/2205.15136 (2022) - [i16]Abdurakhmon Sadiev, Aleksandr Beznosikov
Stochastic Gradient Methods with Preconditioned Updates. CoRR abs/2206.00285 (2022) - [i15]Aleksandr Beznosikov
On Scaled Methods for Saddle Point Problems. CoRR abs/2206.08303 (2022) - [i14]Aleksandr Beznosikov, Alexander V. Gasnikov:
Compression and Data Similarity: Combination of Two Techniques for Communication-Efficient Solving of Distributed Variational Inequalities. CoRR abs/2206.09446 (2022) - [i13]Aleksandr Beznosikov, Boris T. Polyak, Eduard Gorbunov, Dmitry Kovalev, Alexander V. Gasnikov:
Smooth Monotone Stochastic Variational Inequalities and Saddle Point Problems - Survey. CoRR abs/2208.13592 (2022) - [i12]Aleksandr Beznosikov, Alexander V. Gasnikov:
SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities. CoRR abs/2210.05994 (2022) - 2021
- [c3]Aleksandr Beznosikov
One-Point Gradient-Free Methods for Smooth and Non-smooth Saddle-Point Problems. MOTOR 2021: 144-158 - [c2]Aleksandr Beznosikov, Gesualdo Scutari, Alexander Rogozin, Alexander V. Gasnikov:
Distributed Saddle-Point Problems Under Data Similarity. NeurIPS 2021: 8172-8184 - [c1]Aleksandr Beznosikov
Near-Optimal Decentralized Algorithms for Saddle Point Problems over Time-Varying Networks. OPTIMA 2021: 246-257 - [i11]Alexander Rogozin, Aleksandr Beznosikov, Darina Dvinskikh, Dmitry Kovalev
Decentralized Distributed Optimization for Saddle Point Problems. CoRR abs/2102.07758 (2021) - [i10]Aleksandr Beznosikov, Vadim Sushko, Abdurakhmon Sadiev, Alexander V. Gasnikov:
Decentralized Personalized Federated Min-Max Problems. CoRR abs/2106.07289 (2021) - [i9]Aleksandr Beznosikov, Pavel E. Dvurechensky, Anastasia Koloskova, Valentin Samokhin, Sebastian U. Stich, Alexander V. Gasnikov:
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities. CoRR abs/2106.08315 (2021) - [i8]Ivan Stepanov, Artyom Voronov, Aleksandr Beznosikov, Alexander V. Gasnikov:
One-Point Gradient-Free Methods for Composite Optimization with Applications to Distributed Optimization. CoRR abs/2107.05951 (2021) - [i7]Aleksandr Beznosikov, Gesualdo Scutari, Alexander Rogozin, Alexander V. Gasnikov:
Distributed Saddle-Point Problems Under Similarity. CoRR abs/2107.10706 (2021) - [i6]Aleksandr Beznosikov, Peter Richtárik
Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees. CoRR abs/2110.03313 (2021) - [i5]Aleksandr Beznosikov, Martin Takác:
Random-reshuffled SARAH does not need a full gradient computations. CoRR abs/2111.13322 (2021) - 2020
- [i4]Aleksandr Beznosikov
On Biased Compression for Distributed Learning. CoRR abs/2002.12410 (2020) - [i3]Aleksandr Beznosikov, Abdurakhmon Sadiev, Alexander V. Gasnikov:
Gradient-Free Methods for Saddle-Point Problem. CoRR abs/2005.05913 (2020) - [i2]Abdurakhmon Sadiev, Aleksandr Beznosikov
Zeroth-Order Algorithms for Smooth Saddle-Point Problems. CoRR abs/2009.09908 (2020) - [i1]Aleksandr Beznosikov
Local SGD for Saddle-Point Problems. CoRR abs/2010.13112 (2020)
Coauthor Index
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