Malitsky, Yura

9 publications

NeurIPS 2024 Adaptive Proximal Gradient Method for Convex Optimization Yura Malitsky, Konstantin Mishchenko

JMLR 2023 Beyond the Golden Ratio for Variational Inequality Algorithms Ahmet Alacaoglu, Axel Böhm, Yura Malitsky

COLT 2022 Stochastic Variance Reduction for Variational Inequality Methods Ahmet Alacaoglu, Yura Malitsky

NeurIPS 2021 A First-Order Primal-Dual Method with Adaptivity to Local Smoothness Maria-Luiza Vladarean, Yura Malitsky, Volkan Cevher

NeurIPS 2021 Convergence of Adaptive Algorithms for Constrained Weakly Convex Optimization Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher

ICML 2020 A New Regret Analysis for Adam-Type Algorithms Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos, Volkan Cevher

ICML 2020 Adaptive Gradient Descent Without Descent Yura Malitsky, Konstantin Mishchenko

AISTATS 2020 Revisiting Stochastic Extragradient Konstantin Mishchenko, Dmitry Kovalev, Egor Shulgin, Peter Richtarik, Yura Malitsky

ICML 2019 Model Function Based Conditional Gradient Method with Armijo-like Line Search Peter Ochs, Yura Malitsky