Darina Dvinskikh
Darina Dvinskikh
Подтвержден адрес электронной почты в домене wias-berlin.de
Название
Процитировано
Процитировано
Год
Decentralize and randomize: Faster algorithm for Wasserstein barycenters
P Dvurechenskii, D Dvinskikh, A Gasnikov, C Uribe, A Nedich
Advances in Neural Information Processing Systems, 10760-10770, 2018
372018
On the complexity of approximating Wasserstein barycenters
A Kroshnin, N Tupitsa, D Dvinskikh, P Dvurechensky, A Gasnikov, C Uribe
International conference on machine learning, 3530-3540, 2019
212019
Distributed computation of Wasserstein barycenters over networks
CA Uribe, D Dvinskikh, P Dvurechensky, A Gasnikov, A Nedić
2018 IEEE Conference on Decision and Control (CDC), 6544-6549, 2018
212018
Gradient methods for problems with inexact model of the objective
FS Stonyakin, D Dvinskikh, P Dvurechensky, A Kroshnin, O Kuznetsova, ...
International Conference on Mathematical Optimization Theory and Operations …, 2019
182019
Decentralized and parallelized primal and dual accelerated methods for stochastic convex programming problems
D Dvinskikh, A Gasnikov
arXiv preprint arXiv:1904.09015, 2019
112019
Optimal decentralized distributed algorithms for stochastic convex optimization
E Gorbunov, D Dvinskikh, A Gasnikov
arXiv preprint arXiv:1911.07363, 2019
82019
Inexact model: A framework for optimization and variational inequalities
F Stonyakin, A Gasnikov, A Tyurin, D Pasechnyuk, A Agafonov, ...
arXiv preprint arXiv:1902.00990, 2019
62019
On Primal and Dual Approaches for Distributed Stochastic Convex Optimization over Networks
D Dvinskikh, E Gorbunov, A Gasnikov, P Dvurechensky, CA Uribe
2019 IEEE 58th Conference on Decision and Control (CDC), 7435-7440, 2019
52019
Accelerated methods for composite non-bilinear saddle point problem
M Alkousa, D Dvinskikh, F Stonyakin, A Gasnikov
arXiv preprint arXiv:1906.03620, 2019
52019
Oracle complexity separation in convex optimization
A Ivanova, A Gasnikov, P Dvurechensky, D Dvinskikh, A Tyurin, ...
arXiv preprint arXiv:2002.02706, 2020
32020
Adaptive gradient descent for convex and non-convex stochastic optimization
A Ogaltsov, D Dvinskikh, P Dvurechensky, A Gasnikov, V Spokoiny
arXiv preprint arXiv:1911.08380, 2019
32019
On dual approach for distributed stochastic convex optimization over networks
D Dvinskikh, E Gorbunov, A Gasnikov, P Dvurechensky, CA Uribe
arXiv preprint arXiv:1903.09844, 2019
32019
Accelerated and nonaccelerated stochastic gradient descent with model conception
D Dvinskikh, A Tyurin, A Gasnikov
arXiv preprint arXiv:2001.03443, 2020
12020
Accelerated gradient sliding and variance reduction
D Dvinskikh, S Omelchenko, A Tiurin, A Gasnikov
arXiv preprint arXiv:1912.11632, 2019
12019
Accelerated meta-algorithm for convex optimization
D Dvinskikh, D Kamzolov, A Gasnikov, P Dvurechensky, D Pasechnyk, ...
arXiv preprint arXiv:2004.08691, 2020
2020
Accelerated and nonaccelerated stochastic gradient descent with inexact model
D Dvinskikh, A Tyurin, A Gasnikov, S Omelchenko
arXiv preprint arXiv:2004.04490, 2020
2020
Inexact Relative Smoothness and Strong Convexity for Optimization and Variational Inequalities by Inexact Model
F Stonyakin, A Tyurin, A Gasnikov, P Dvurechensky, A Agafonov, ...
arXiv preprint arXiv:2001.09013, 2020
2020
SA vs SAA for population Wasserstein barycenter calculation
D Dvinskikh
arXiv preprint arXiv:2001.07697, 2020
2020
Two approaches for population Wasserstein barycenter problem: Stochastic Averaging versus Sample Average Approximation
D Dvinskikh, A Gasnikov
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Статьи 1–19