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Aleksandr Beznosikov

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Sparse Concept Bottleneck Models: Gumbel Tricks in Contrastive Learning

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Apr 04, 2024
Andrei Semenov, Vladimir Ivanov, Aleksandr Beznosikov, Alexander Gasnikov

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Optimal Data Splitting in Distributed Optimization for Machine Learning

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Jan 15, 2024
Daniil Medyakov, Gleb Molodtsov, Aleksandr Beznosikov, Alexander Gasnikov

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Activations and Gradients Compression for Model-Parallel Training

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Jan 15, 2024
Mikhail Rudakov, Aleksandr Beznosikov, Yaroslav Kholodov, Alexander Gasnikov

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Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting

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Oct 09, 2023
Aleksei Ustimenko, Aleksandr Beznosikov

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First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities

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May 25, 2023
Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander Gasnikov, Alexey Naumov, Eric Moulines

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Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features

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Apr 23, 2023
Aleksandr Beznosikov, David Dobre, Gauthier Gidel

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Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities

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Feb 15, 2023
Aleksandr Beznosikov, Alexander Gasnikov

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SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities

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Oct 12, 2022
Aleksandr Beznosikov, Alexander Gasnikov

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Smooth Monotone Stochastic Variational Inequalities and Saddle Point Problems -- Survey

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Aug 29, 2022
Aleksandr Beznosikov, Boris Polyak, Eduard Gorbunov, Dmitry Kovalev, Alexander Gasnikov

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Compression and Data Similarity: Combination of Two Techniques for Communication-Efficient Solving of Distributed Variational Inequalities

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Jun 19, 2022
Aleksandr Beznosikov, Alexander Gasnikov

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