Παρακολούθηση
Egor Shulgin
Egor Shulgin
PhD candidate, KAUST
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα kaust.edu.sa - Αρχική σελίδα
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Παρατίθεται από
Παρατίθεται από
Έτος
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
4752019
Revisiting stochastic extragradient
K Mishchenko, D Kovalev, E Shulgin, P Richtárik, Y Malitsky
International Conference on Artificial Intelligence and Statistics, 4573-4582, 2020
912020
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
582022
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
372021
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
362021
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
302021
Shifted compression framework: Generalizations and improvements
E Shulgin, P Richtárik
Uncertainty in Artificial Intelligence, 1813-1823, 2022
72022
Certified Robustness in Federated Learning
M Alfarra, JC Pérez, E Shulgin, P Richtárik, B Ghanem
NeurIPS 2022 Workshop Federated Learning, 2022
72022
Towards a Better Theoretical Understanding of Independent Subnetwork Training
E Shulgin, P Richtárik
International Conference on Machine Learning (ICML), 2023
62023
SPAM: Stochastic Proximal Point Method with Momentum Variance Reduction for Non-convex Cross-Device Federated Learning
A Karagulyan, E Shulgin, A Sadiev, P Richtárik
arXiv preprint arXiv:2405.20127, 2024
42024
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
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