Aleksandr Beznosikov

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 49

Top Topics

Nonlinear Programming

Constrained Optimization

Top Venues

Comput. Manag. Sci.

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)
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)
Aleksei Ustimenko, Aleksandr Beznosikov
Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting. ICLR (2024)
Aleksandr Beznosikov, Martin Takác
Random-reshuffled SARAH does not need full gradient computations. Optim. Lett. 18 (3) (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)
Andrei Semenov, Vladimir Ivanov, Aleksandr Beznosikov, Alexander V. Gasnikov
Sparse Concept Bottleneck Models: Gumbel Tricks in Contrastive Learning. CoRR (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)
Abdurakhmon Sadiev, Aleksandr Beznosikov, Abdulla Jasem Almansoori, Dmitry Kamzolov, Rachael Tappenden, Martin Takác
Stochastic Gradient Methods with Preconditioned Updates. J. Optim. Theory Appl. 201 (2) (2024)
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 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)
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)
Aleksandr Beznosikov, Eduard Gorbunov, Hugo Berard, Nicolas Loizou
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods. AISTATS (2023)
Aleksandr Beznosikov, David Dobre, Gauthier Gidel
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features. CoRR (2023)
Aleksandr Beznosikov, Martin Takác, Alexander V. Gasnikov
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities. NeurIPS (2023)
Aleksei Ustimenko, Aleksandr Beznosikov
Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting. CoRR (2023)
Aleksandr Beznosikov, Eduard Gorbunov, Hugo Berard, Nicolas Loizou
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods. CoRR (2022)
Aleksandr Beznosikov, Alexander V. Gasnikov
Compression and Data Similarity: Combination of Two Techniques for Communication-Efficient Solving of Distributed Variational Inequalities. OPTIMA (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)
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)
Aleksandr Beznosikov, Aibek Alanov, Dmitry Kovalev, Martin Takác, Alexander V. Gasnikov
On Scaled Methods for Saddle Point Problems. CoRR (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)
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)
Aleksandr Beznosikov, Boris Polyak, Eduard Gorbunov, Dmitry Kovalev, Alexander V. Gasnikov
Smooth Monotone Stochastic Variational Inequalities and Saddle Point Problems - Survey. CoRR (2022)
Aleksandr Beznosikov, Alexander V. Gasnikov
SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities. CoRR (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)
Dmitry Kovalev, Aleksandr Beznosikov, Abdurakhmon Sadiev, Michael Persiianov, Peter Richtárik, Alexander V. Gasnikov
Optimal Algorithms for Decentralized Stochastic Variational Inequalities. CoRR (2022)
Abdurakhmon Sadiev, Aleksandr Beznosikov, Abdulla Jasem Almansoori, Dmitry Kamzolov, Rachael Tappenden, Martin Takác
Stochastic Gradient Methods with Preconditioned Updates. CoRR (2022)
Aleksandr Beznosikov, Vadim Sushko, Abdurakhmon Sadiev, Alexander V. Gasnikov
Decentralized Personalized Federated Min-Max Problems. CoRR (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)
Aleksandr Beznosikov, Martin Takác
Random-reshuffled SARAH does not need a full gradient computations. CoRR (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)
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)
Aleksandr Beznosikov, Alexander Rogozin, Dmitry Kovalev, Alexander V. Gasnikov
Near-Optimal Decentralized Algorithms for Saddle Point Problems over Time-Varying Networks. OPTIMA (2021)
Abdurakhmon Sadiev, Aleksandr Beznosikov, Pavel E. Dvurechensky, Alexander V. Gasnikov
Zeroth-Order Algorithms for Smooth Saddle-Point Problems. CoRR (2020)
Aleksandr Beznosikov, Valentin Samokhin, Alexander V. Gasnikov
Local SGD for Saddle-Point Problems. CoRR (2020)
Aleksandr Beznosikov, Samuel Horváth, Peter Richtárik, Mher Safaryan
On Biased Compression for Distributed Learning. CoRR (2020)
Aleksandr Beznosikov, Abdurakhmon Sadiev, Alexander V. Gasnikov
Gradient-Free Methods for Saddle-Point Problem. CoRR (2020)