Rustem Islamov

According to our database, Rustem Islamov authored at least 10 papers between 2021 and 2024.

Collaborative distances:

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

2024

Near Optimal Decentralized Optimization with Compression and Momentum Tracking.

Rustem Islamov, Yuan Gao, Sebastian U. Stich

CoRR, 2024

EControl: Fast Distributed Optimization with Compression and Error Control.

Yuan Gao, Rustem Islamov, Sebastian U. Stich

Proceedings of the Twelfth International Conference on Learning Representations, 2024

AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms.

Rustem Islamov, Mher Safaryan, Dan Alistarh

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

Distributed Newton-Type Methods with Communication Compression and Bernoulli Aggregation.

Rustem Islamov, Xun Qian, Slavomír Hanzely, Mher Safaryan, Peter Richtárik

Trans. Mach. Learn. Res., 2023

Clip21: Error Feedback for Gradient Clipping.

Sarit Khirirat, Eduard Gorbunov, Samuel Horváth, Rustem Islamov, Fakhri Karray, Peter Richtárik

CoRR, 2023

Partially Personalized Federated Learning: Breaking the Curse of Data Heterogeneity.

Konstantin Mishchenko, Rustem Islamov, Eduard Gorbunov, Samuel Horváth

CoRR, 2023

2022

FedNL: Making Newton-Type Methods Applicable to Federated Learning.

Mher Safaryan, Rustem Islamov, Xun Qian, Peter Richtárik

Proceedings of the International Conference on Machine Learning, 2022

Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning.

Xun Qian, Rustem Islamov, Mher Safaryan, Peter Richtárik

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

2021

Distributed Second Order Methods with Fast Rates and Compressed Communication.

Rustem Islamov, Xun Qian, Peter Richtárik

Proceedings of the 38th International Conference on Machine Learning, 2021