Egor Shulgin

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 15

Top Topics

Variance Reduction

Optimization Method

Top Venues

Publications

Avetik G. Karagulyan, Egor Shulgin, Abdurakhmon Sadiev, Peter Richtárik
SPAM: Stochastic Proximal Point Method with Momentum Variance Reduction for Non-convex Cross-Device Federated Learning. CoRR (2024)
Egor Shulgin, Peter Richtárik
Towards a Better Theoretical Understanding of Independent Subnetwork Training. CoRR (2023)
Yury Demidovich, Grigory Malinovsky, Egor Shulgin, Peter Richtárik
MAST: Model-Agnostic Sparsified Training. CoRR (2023)
Egor Shulgin, Peter Richtárik
Shifted Compression Framework: Generalizations and Improvements. CoRR (2022)
Egor Shulgin, Peter Richtárik
Shifted compression framework: generalizations and improvements. UAI (2022)
Motasem Alfarra, Juan C. Pérez, Egor Shulgin, Peter Richtárik, Bernard Ghanem
Certified Robustness in Federated Learning. CoRR (2022)
Alexander Rogozin, Vladislav Lukoshkin, Alexander V. Gasnikov, Dmitry Kovalev, Egor Shulgin
Towards Accelerated Rates for Distributed Optimization over Time-Varying Networks. OPTIMA (2021)
Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Alexander Rogozin, Alexander V. Gasnikov
ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks. CoRR (2021)
Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Alexander Rogozin, Alexander V. Gasnikov
ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks. ICML (2021)
Anastasiya Ivanova, Dmitry Pasechnyuk, Dmitry Grishchenko, Egor Shulgin, Alexander V. Gasnikov, Vladislav Matyukhin
Adaptive Catalyst for Smooth Convex Optimization. OPTIMA (2021)
Konstantin Mishchenko, Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Yura Malitsky
Revisiting Stochastic Extragradient. AISTATS (2020)
Mher Safaryan, Egor Shulgin, Peter Richtárik
Uncertainty Principle for Communication Compression in Distributed and Federated Learning and the Search for an Optimal Compressor. CoRR (2020)
Konstantin Mishchenko, Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Yura Malitsky
Revisiting Stochastic Extragradient. CoRR (2019)
Xun Qian, Peter Richtárik, Robert M. Gower, Alibek Sailanbayev, Nicolas Loizou, Egor Shulgin
SGD with Arbitrary Sampling: General Analysis and Improved Rates. ICML (2019)
Robert Mansel Gower, Nicolas Loizou, Xun Qian, Alibek Sailanbayev, Egor Shulgin, Peter Richtárik
SGD: General Analysis and Improved Rates. CoRR (2019)