Follow
Egor Shulgin
Egor Shulgin
PhD candidate, KAUST
Verified email at kaust.edu.sa - Homepage
Title
Cited by
Cited by
Year
SGD: General analysis and improved rates
RM Gower, N Loizou, X Qian, A Sailanbayev, E Shulgin, P Richtárik
International Conference on Machine Learning, 5200-5209, 2019
3982019
Revisiting stochastic extragradient
K Mishchenko, D Kovalev, E Shulgin, P Richtárik, Y Malitsky
International Conference on Artificial Intelligence and Statistics, 4573-4582, 2020
732020
Uncertainty principle for communication compression in distributed and federated learning and the search for an optimal compressor
M Safaryan, E Shulgin, P Richtárik
Information and Inference: A Journal of the IMA 11 (2), 557-580, 2022
472022
Adaptive catalyst for smooth convex optimization
A Ivanova, D Pasechnyuk, D Grishchenko, E Shulgin, A Gasnikov, ...
International Conference on Optimization and Applications, 20-37, 2021
352021
ADOM: Accelerated decentralized optimization method for time-varying networks
D Kovalev, E Shulgin, P Richtárik, AV Rogozin, A Gasnikov
International Conference on Machine Learning, 5784-5793, 2021
332021
Towards accelerated rates for distributed optimization over time-varying networks
A Rogozin, V Lukoshkin, A Gasnikov, D Kovalev, E Shulgin
Optimization and Applications: 12th International Conference, OPTIMA 2021 …, 2021
272021
Shifted compression framework: Generalizations and improvements
E Shulgin, P Richtárik
Uncertainty in Artificial Intelligence, 1813-1823, 2022
62022
Towards a Better Theoretical Understanding of Independent Subnetwork Training
E Shulgin, P Richtárik
arXiv preprint arXiv:2306.16484, 2023
42023
Certified Robustness in Federated Learning
M Alfarra, JC Pérez, E Shulgin, P Richtárik, B Ghanem
NeurIPS 2022 Workshop Federated Learning, 2022
42022
Lecture notes on stochastic processes
A Gasnikov, E Gorbunov, S Guz, E Chernousova, M Shirobokov, ...
arXiv preprint arXiv:1907.01060, 2019
12019
MAST: Model-Agnostic Sparsified Training
Y Demidovich, G Malinovsky, E Shulgin, P Richtárik
arXiv preprint arXiv:2311.16086, 2023
2023
MotasemAlfarra/federated-learning-with-pytorch
M Alfarra, JC Pérez, E Shulgin, P Richtarik, B Ghanem
Github, 2022
2022
SGD: General Analysis and Improved Rates
R Mansel Gower, N Loizou, X Qian, A Sailanbayev, E Shulgin, P Richtarik
arXiv e-prints, arXiv: 1901.09401, 2019
2019
The system can't perform the operation now. Try again later.
Articles 1–13