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06/15/2021
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities
We consider decentralized stochastic variational inequalities where the ...
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06/14/2021
Decentralized Personalized Federated Min-Max Problems
Personalized Federated Learning has recently seen tremendous progress, a...
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06/10/2021
Near-Optimal High Probability Complexity Bounds for Non-Smooth Stochastic Optimization with Heavy-Tailed Noise
Thanks to their practical efficiency and random nature of the data, stoc...
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06/08/2021
Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks
We consider the task of minimizing the sum of smooth and strongly convex...
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06/03/2021
Convex optimization
This textbook is based on lectures given by the authors at MIPT (Moscow)...
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02/27/2021
Parallel Stochastic Mirror Descent for MDPs
We consider the problem of learning the optimal policy for infinite-hori...
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02/18/2021
ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks
We propose ADOM - an accelerated method for smooth and strongly convex d...
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02/15/2021
Decentralized Distributed Optimization for Saddle Point Problems
We consider distributed convex-concave saddle point problems over arbitr...
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02/12/2021
Newton Method over Networks is Fast up to the Statistical Precision
We propose a distributed cubic regularization of the Newton method for s...
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12/11/2020
Recent Theoretical Advances in Non-Convex Optimization
Motivated by recent increased interest in optimization algorithms for no...
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10/25/2020
Local SGD for Saddle-Point Problems
GAN is one of the most popular and commonly used neural network models. ...
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09/21/2020
Zeroth-Order Algorithms for Smooth Saddle-Point Problems
In recent years, the importance of saddle-point problems in machine lear...
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06/11/2020
Stochastic Saddle-Point Optimization for Wasserstein Barycenters
We study the computation of non-regularized Wasserstein barycenters of p...
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05/21/2020
Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping
In this paper, we propose a new accelerated stochastic first-order metho...
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05/12/2020
Gradient-Free Methods for Saddle-Point Problem
In the paper, we generalize the approach Gasnikov et. al, 2017, which al...
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06/09/2019
Accelerated Alternating Minimization
Alternating minimization (AM) optimization algorithms have been known fo...
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01/24/2019
On the Complexity of Approximating Wasserstein Barycenter
We study the complexity of approximating Wassertein barycenter of m disc...
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09/03/2018
A Dual Approach for Optimal Algorithms in Distributed Optimization over Networks
We study the optimal convergence rates for distributed convex optimizati...
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06/11/2018
Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters
We study the problem of decentralized distributed computation of a discr...
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04/08/2018
An Accelerated Directional Derivative Method for Smooth Stochastic Convex Optimization
We consider smooth stochastic convex optimization problems in the contex...
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03/08/2018
Distributed Computation of Wasserstein Barycenters over Networks
We propose a new class-optimal algorithm for the distributed computation...
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02/25/2018
An Accelerated Method for Derivative-Free Smooth Stochastic Convex Optimization
We consider an unconstrained problem of minimization of a smooth convex ...
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02/12/2018
Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn's Algorithm
We analyze two algorithms for approximating the general optimal transpor...
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12/01/2017
Optimal Algorithms for Distributed Optimization
In this paper, we study the optimal convergence rate for distributed con...
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07/26/2017