Yura Malitsky - RankMe

32 papers A* 7A 1Journal 24

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Entropic Mirror Descent for Linear Systems: Polyak's Stepsize and Implicit Bias. CoRR Yura Malitsky, Alexander Posch
2025	J	`jnl`	Towards Weaker Variance Assumptions for Stochastic Optimization. CoRR Ahmet Alacaoglu, Yura Malitsky, Stephen J. Wright
2024	A*	`conf`	Adaptive Proximal Gradient Method for Convex Optimization. NeurIPS Yura Malitsky, Konstantin Mishchenko
2023	J	`jnl`	A First-Order Algorithm for Decentralised Min-Max Problems. CoRR Yura Malitsky, Matthew K. Tam
2023	J	`jnl`	Adaptive Proximal Gradient Method for Convex Optimization. CoRR Yura Malitsky, Konstantin Mishchenko
2023	J	`jnl`	Beyond the Golden Ratio for Variational Inequality Algorithms. J. Mach. Learn. Res. Ahmet Alacaoglu, Axel Böhm, Yura Malitsky
2023	J	`jnl`	Distributed forward-backward methods for ring networks. Comput. Optim. Appl. Francisco J. Aragón Artacho, Yura Malitsky, Matthew K. Tam, David Torregrosa-Belén
2023	J	`jnl`	Over-the-Air Computation With Multiple Receivers: A Space-Time Approach. IEEE Wirel. Commun. Lett. Zheng Chen, Yura Malitsky
2023	J	`jnl`	Over-the-Air Computation for Distributed Systems: Something Old and Something New. IEEE Netw. Zheng Chen, Erik G. Larsson, Carlo Fischione, Mikael Johansson, Yura Malitsky
2023	J	`jnl`	Resolvent splitting for sums of monotone operators with minimal lifting. Math. Program. Yura Malitsky, Matthew K. Tam
2022	J	`jnl`	Beyond the Golden Ratio for Variational Inequality Algorithms. CoRR Ahmet Alacaoglu, Axel Böhm, Yura Malitsky
2022	J	`jnl`	Over-the-Air Computation for Distributed Systems: Something Old and Something New. CoRR Zheng Chen, Erik G. Larsson, Carlo Fischione, Mikael Johansson, Yura Malitsky
2022	J	`jnl`	Over-the-Air Computation with Multiple Receivers: A Space-Time Approach. CoRR Zheng Chen, Yura Malitsky
2022	A*	`conf`	Stochastic Variance Reduction for Variational Inequality Methods. COLT Ahmet Alacaoglu, Yura Malitsky
2021	A*	`conf`	A first-order primal-dual method with adaptivity to local smoothness. NeurIPS Maria-Luiza Vladarean, Yura Malitsky, Volkan Cevher
2021	J	`jnl`	A first-order primal-dual method with adaptivity to local smoothness. CoRR Maria-Luiza Vladarean, Yura Malitsky, Volkan Cevher
2021	A*	`conf`	Convergence of adaptive algorithms for constrained weakly convex optimization. NeurIPS Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher
2021	J	`jnl`	Distributed Forward-Backward Methods without Central Coordination. CoRR Francisco J. Aragón Artacho, Yura Malitsky, Matthew K. Tam, David Torregrosa-Belén
2021	J	`jnl`	Forward-reflected-backward method with variance reduction. Comput. Optim. Appl. Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher
2021	J	`jnl`	Stochastic Variance Reduction for Variational Inequality Methods. CoRR Ahmet Alacaoglu, Yura Malitsky
2020	J	`jnl`	A Forward-Backward Splitting Method for Monotone Inclusions Without Cocoercivity. SIAM J. Optim. Yura Malitsky, Matthew K. Tam
2020	A*	`conf`	A new regret analysis for Adam-type algorithms. ICML Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos, Volkan Cevher
2020	J	`jnl`	A new regret analysis for Adam-type algorithms. CoRR Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos, Volkan Cevher
2020	A*	`conf`	Adaptive Gradient Descent without Descent. ICML Yura Malitsky, Konstantin Mishchenko
2020	J	`jnl`	Convergence of adaptive algorithms for weakly convex constrained optimization. CoRR Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher
2020	J	`jnl`	Golden ratio algorithms for variational inequalities. Math. Program. Yura Malitsky
2020	A	`conf`	Revisiting Stochastic Extragradient. AISTATS Konstantin Mishchenko, Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Yura Malitsky
2019	J	`jnl`	Adaptive gradient descent without descent. CoRR Yura Malitsky, Konstantin Mishchenko
2019	A*	`conf`	Model Function Based Conditional Gradient Method with Armijo-like Line Search. ICML Peter Ochs, Yura Malitsky
2019	J	`jnl`	Model Function Based Conditional Gradient Method with Armijo-like Line Search. CoRR Yura Malitsky, Peter Ochs
2019	J	`jnl`	Revisiting Stochastic Extragradient. CoRR Konstantin Mishchenko, Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Yura Malitsky
2018	J	`jnl`	A First-Order Primal-Dual Algorithm with Linesearch. SIAM J. Optim. Yura Malitsky, Thomas Pock