Konstantin Burlachenko

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 18

Top Topics

Taylor Series Expansion

Distributed Learning

Variance Reduction

Optimization Algorithm

Top Venues

DistributedML@CoNEXT

Trans. Mach. Learn. Res.

SIAM J. Math. Data Sci.

Publications

Haoyu Zhao, Konstantin Burlachenko, Zhize Li, Peter Richtárik
Faster Rates for Compressed Federated Learning with Client-Variance Reduction. SIAM J. Math. Data Sci. 6 (1) (2024)
Peter Richtárik, Elnur Gasanov, Konstantin Burlachenko
Error Feedback Reloaded: From Quadratic to Arithmetic Mean of Smoothness Constants. CoRR (2024)
Vladimir Malinovskii, Denis Mazur, Ivan Ilin, Denis Kuznedelev, Konstantin Burlachenko, Kai Yi, Dan Alistarh, Peter Richtárik
PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression. CoRR (2024)
Peter Richtárik, Elnur Gasanov, Konstantin Burlachenko
Error Feedback Reloaded: From Quadratic to Arithmetic Mean of Smoothness Constants. ICLR (2024)
Alexander Tyurin, Lukang Sun, Konstantin Burlachenko, Peter Richtárik
Sharper Rates and Flexible Framework for Nonconvex SGD with Client and Data Sampling. Trans. Mach. Learn. Res. 2023 (2023)
El Houcine Bergou, Konstantin Burlachenko, Aritra Dutta, Peter Richtárik
Personalized Federated Learning with Communication Compression. Trans. Mach. Learn. Res. 2023 (2023)
Konstantin Burlachenko, Abdulmajeed Alrowithi, Fahad Ali Albalawi, Peter Richtárik
Federated Learning is Better with Non-Homomorphic Encryption. DistributedML@CoNEXT (2023)
Konstantin Burlachenko, Abdulmajeed Alrowithi, Fahad Ali Albalawi, Peter Richtárik
Federated Learning is Better with Non-Homomorphic Encryption. CoRR (2023)
Peter Richtárik, Elnur Gasanov, Konstantin Burlachenko
Error Feedback Shines when Features are Rare. CoRR (2023)
Grigory Malinovsky, Samuel Horváth, Konstantin Burlachenko, Peter Richtárik
Federated Learning with Regularized Client Participation. CoRR (2023)
Konstantin Burlachenko, Samuel Horváth, Peter Richtárik
FL_PyTorch: optimization research simulator for federated learning. CoRR (2022)
Abdurakhmon Sadiev, Grigory Malinovsky, Eduard Gorbunov, Igor Sokolov, Ahmed Khaled, Konstantin Burlachenko, Peter Richtárik
Federated Optimization Algorithms with Random Reshuffling and Gradient Compression. CoRR (2022)
Alexander Tyurin, Lukang Sun, Konstantin Burlachenko, Peter Richtárik
Sharper Rates and Flexible Framework for Nonconvex SGD with Client and Data Sampling. CoRR (2022)
El Houcine Bergou, Konstantin Burlachenko, Aritra Dutta, Peter Richtárik
Personalized Federated Learning with Communication Compression. CoRR (2022)
Eduard A. Gorbunov, Konstantin Burlachenko, Zhize Li, Peter Richtárik
MARINA: Faster Non-Convex Distributed Learning with Compression. CoRR (2021)
Haoyu Zhao, Konstantin Burlachenko, Zhize Li, Peter Richtárik
Faster Rates for Compressed Federated Learning with Client-Variance Reduction. CoRR (2021)
Konstantin Burlachenko, Samuel Horváth, Peter Richtárik
FL_PyTorch: optimization research simulator for federated learning. DistributedML@CoNEXT (2021)
Eduard A. Gorbunov, Konstantin Burlachenko, Zhize Li, Peter Richtárik
MARINA: Faster Non-Convex Distributed Learning with Compression. ICML (2021)