Yura Malitsky

According to our database, Yura Malitsky authored at least 23 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2026

A first-order algorithm for decentralised min-max problems.

Yura Malitsky, Matthew K. Tam

Numerische Mathematik, June, 2026

2025

Entropic Mirror Descent for Linear Systems: Polyak's Stepsize and Implicit Bias.

Yura Malitsky, Alexander Posch

CoRR, May, 2025

Towards Weaker Variance Assumptions for Stochastic Optimization.

Ahmet Alacaoglu, Yura Malitsky, Stephen J. Wright

CoRR, April, 2025

2024

Adaptive Proximal Gradient Method for Convex Optimization.

Yura Malitsky, Konstantin Mishchenko

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Distributed forward-backward methods for ring networks.

Francisco J. Aragón Artacho, Yura Malitsky, Matthew K. Tam, David Torregrosa-Belén

Comput. Optim. Appl., December, 2023

Over-the-Air Computation for Distributed Systems: Something Old and Something New.

Zheng Chen, Erik G. Larsson, Carlo Fischione, Mikael Johansson, Yura Malitsky

IEEE Netw., September, 2023

Over-the-Air Computation With Multiple Receivers: A Space-Time Approach.

Zheng Chen, Yura Malitsky

IEEE Wirel. Commun. Lett., August, 2023

Resolvent splitting for sums of monotone operators with minimal lifting.

Yura Malitsky, Matthew K. Tam

Math. Program., 2023

Beyond the Golden Ratio for Variational Inequality Algorithms.

Ahmet Alacaoglu, Axel Böhm, Yura Malitsky

J. Mach. Learn. Res., 2023

2022

Over-the-Air Computation with Multiple Receivers: A Space-Time Approach.

Zheng Chen, Yura Malitsky

CoRR, 2022

Stochastic Variance Reduction for Variational Inequality Methods.

Ahmet Alacaoglu, Yura Malitsky

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Distributed Forward-Backward Methods without Central Coordination.

Francisco J. Aragón Artacho, Yura Malitsky, Matthew K. Tam, David Torregrosa-Belén

CoRR, 2021

Forward-reflected-backward method with variance reduction.

Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher

Comput. Optim. Appl., 2021

A first-order primal-dual method with adaptivity to local smoothness.

Maria-Luiza Vladarean, Yura Malitsky, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Convergence of adaptive algorithms for constrained weakly convex optimization.

Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

A Forward-Backward Splitting Method for Monotone Inclusions Without Cocoercivity.

Yura Malitsky, Matthew K. Tam

SIAM J. Optim., 2020

Golden ratio algorithms for variational inequalities.

Yura Malitsky

Math. Program., 2020

Convergence of adaptive algorithms for weakly convex constrained optimization.

Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher

CoRR, 2020

Adaptive Gradient Descent without Descent.

Yura Malitsky, Konstantin Mishchenko

Proceedings of the 37th International Conference on Machine Learning, 2020

A new regret analysis for Adam-type algorithms.

Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos, Volkan Cevher

Proceedings of the 37th International Conference on Machine Learning, 2020

Revisiting Stochastic Extragradient.

Konstantin Mishchenko, Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Yura Malitsky

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Model Function Based Conditional Gradient Method with Armijo-like Line Search.

Peter Ochs, Yura Malitsky

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

A First-Order Primal-Dual Algorithm with Linesearch.

Yura Malitsky, Thomas Pock

SIAM J. Optim., 2018