Distributed Computation of Wasserstein Barycenters Over Networks. - Cesar A. Uribe; Darina Dvinskikh; Pavel E. Dvurechensky; Alexander V. Gasnikov; Angelia Nedic (CDC, 2018)

Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters. - Pavel E. Dvurechenskii; Darina Dvinskikh; Alexander V. Gasnikov; César A. Uribe; Angelia Nedich (NeurIPS, 2018)

On Primal and Dual Approaches for Distributed Stochastic Convex Optimization over Networks. - Darina Dvinskikh; Eduard Gorbunov; Alexander V. Gasnikov; Pavel E. Dvurechensky; César A. Uribe (CDC, 2019)

On the Complexity of Approximating Wasserstein Barycenters. - Alexey Kroshnin; Nazarii Tupitsa; Darina Dvinskikh; Pavel E. Dvurechensky; Alexander V. Gasnikov; Cesar A. Uribe (ICML, 2019)

Gradient Methods for Problems with Inexact Model of the Objective. - Fedor S. Stonyakin; Darina Dvinskikh; Pavel E. Dvurechensky; Alexey Kroshnin; Olesya Kuznetsova; Artem Agafonov; Alexander V. Gasnikov; Alexander Tyurin; César A. Uribe; Dmitry Pasechnyuk; Sergei Artamonov (MOTOR, 2019)

On the Complexity of Approximating Wasserstein Barycenter. - Alexey Kroshnin; Darina Dvinskikh; Pavel E. Dvurechensky; Alexander V. Gasnikov; Nazarii Tupitsa; César A. Uribe (CoRR, 2019)

SA vs SAA for population Wasserstein barycenter calculation. - Darina Dvinskikh (CoRR, 2020)

Improved Complexity Bounds in Wasserstein Barycenter Problem. - Darina Dvinskikh; Daniil Tiapkin (AISTATS, 2021)

Decentralized Distributed Optimization for Saddle Point Problems. - Alexander Rogozin; Aleksandr Beznosikov; Darina Dvinskikh; Dmitry Kovalev; Pavel E. Dvurechensky; Alexander V. Gasnikov (CoRR, 2021)

Inexact model: a framework for optimization and variational inequalities. - Fedor S. Stonyakin; Alexander Tyurin; Alexander V. Gasnikov; Pavel E. Dvurechensky; Artem Agafonov; Darina Dvinskikh; Mohammad S. Alkousa; Dmitry Pasechnyuk; Sergei Artamonov; Victoria V. Piskunova (Optim. Methods Softw., 2021)

Decentralized personalized federated learning: Lower bounds and optimal algorithm for all personalization modes. - Abdurakhmon Sadiev; Ekaterina Borodich; Aleksandr Beznosikov; Darina Dvinskikh; Saveliy Chezhegov; Rachael Tappenden; Martin Takác 001; Alexander V. Gasnikov (EURO J. Comput. Optim., 2022)

Oracle Complexity Separation in Convex Optimization. - Anastasiya Ivanova; Pavel E. Dvurechensky; Evgeniya A. Vorontsova; Dmitry Pasechnyuk; Alexander V. Gasnikov; Darina Dvinskikh; Alexander Tyurin (J. Optim. Theory Appl., 2022)

Stochastic approximation versus sample average approximation for Wasserstein barycenters. - Darina Dvinskikh (Optim. Methods Softw., 2022)

Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance. - Nikita Kornilov; Ohad Shamir; Aleksandr V. Lobanov; Darina Dvinskikh; Alexander V. Gasnikov; Innokentiy Shibaev; Eduard Gorbunov; Samuel Horváth (NeurIPS, 2023)

Gradient-free methods for non-smooth convex stochastic optimization with heavy-tailed noise on convex compact. - Nikita Kornilov; Alexander V. Gasnikov; Pavel E. Dvurechensky; Darina Dvinskikh (Comput. Manag. Sci., 2023)

Accelerated zero-order SGD under high-order smoothness and overparameterized regime. - Georgii Bychkov; Darina Dvinskikh; Anastasia Antsiferova; Alexander V. Gasnikov; Aleksandr V. Lobanov (CoRR, 2024)