Elnur Gasanov

According to our database, Elnur Gasanov authored at least 9 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Error Feedback Reloaded: From Quadratic to Arithmetic Mean of Smoothness Constants.

Peter Richtárik, Elnur Gasanov, Konstantin Burlachenko

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Understanding Progressive Training Through the Framework of Randomized Coordinate Descent.

Rafal Szlendak, Elnur Gasanov, Peter Richtárik

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Adaptive Compression for Communication-Efficient Distributed Training.

Maksim Makarenko, Elnur Gasanov, Abdurakhmon Sadiev, Rustem Islamov, Peter Richtárik

Trans. Mach. Learn. Res., 2023

Error Feedback Shines when Features are Rare.

Peter Richtárik, Elnur Gasanov, Konstantin Burlachenko

CoRR, 2023

2022

3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation.

Peter Richtárik, Igor Sokolov, Elnur Gasanov, Ilyas Fatkhullin, Zhize Li, Eduard Gorbunov

Proceedings of the International Conference on Machine Learning, 2022

FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning.

Elnur Gasanov, Ahmed Khaled, Samuel Horváth, Peter Richtárik

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks.

Dmitry Kovalev, Elnur Gasanov, Alexander V. Gasnikov, Peter Richtárik

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

2020

From Local SGD to Local Fixed-Point Methods for Federated Learning.

Grigory Malinovskiy, Dmitry Kovalev, Elnur Gasanov, Laurent Condat, Peter Richtárik

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

2018

Stochastic Spectral and Conjugate Descent Methods.

Dmitry Kovalev, Peter Richtárik, Eduard Gorbunov, Elnur Gasanov

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018