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Rustem Islamov
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2020 – today
- 2024
- [c5]Rustem Islamov, Mher Safaryan, Dan Alistarh:
AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms. AISTATS 2024: 649-657 - [c4]Yuan Gao, Rustem Islamov, Sebastian U. Stich:
EControl: Fast Distributed Optimization with Compression and Error Control. ICLR 2024 - [i12]Rustem Islamov, Yuan Gao, Sebastian U. Stich:
Near Optimal Decentralized Optimization with Compression and Momentum Tracking. CoRR abs/2405.20114 (2024) - [i11]Rustem Islamov, Niccolò Ajroldi, Antonio Orvieto, Aurélien Lucchi:
Loss Landscape Characterization of Neural Networks without Over-Parametrization. CoRR abs/2410.12455 (2024) - [i10]Enea Monzio Compagnoni, Tianlin Liu, Rustem Islamov, Frank Norbert Proske, Antonio Orvieto, Aurélien Lucchi:
Adaptive Methods through the Lens of SDEs: Theoretical Insights on the Role of Noise. CoRR abs/2411.15958 (2024) - 2023
- [j2]Rustem Islamov, Xun Qian, Slavomír Hanzely, Mher Safaryan, Peter Richtárik:
Distributed Newton-Type Methods with Communication Compression and Bernoulli Aggregation. Trans. Mach. Learn. Res. 2023 (2023) - [j1]Maksim Makarenko, Elnur Gasanov, Abdurakhmon Sadiev, Rustem Islamov, Peter Richtárik:
Adaptive Compression for Communication-Efficient Distributed Training. Trans. Mach. Learn. Res. 2023 (2023) - [i9]Konstantin Mishchenko, Rustem Islamov, Eduard Gorbunov, Samuel Horváth:
Partially Personalized Federated Learning: Breaking the Curse of Data Heterogeneity. CoRR abs/2305.18285 (2023) - [i8]Sarit Khirirat, Eduard Gorbunov, Samuel Horváth, Rustem Islamov, Fakhri Karray, Peter Richtárik:
Clip21: Error Feedback for Gradient Clipping. CoRR abs/2305.18929 (2023) - [i7]Rustem Islamov, Mher Safaryan
, Dan Alistarh:
AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms. CoRR abs/2310.20452 (2023) - [i6]Yuan Gao, Rustem Islamov, Sebastian U. Stich:
EControl: Fast Distributed Optimization with Compression and Error Control. CoRR abs/2311.05645 (2023) - 2022
- [c3]Xun Qian, Rustem Islamov
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning. AISTATS 2022: 680-720 - [c2]Mher Safaryan, Rustem Islamov
FedNL: Making Newton-Type Methods Applicable to Federated Learning. ICML 2022: 18959-19010 - [i5]Rustem Islamov, Xun Qian, Slavomír Hanzely, Mher Safaryan, Peter Richtárik:
Distributed Newton-Type Methods with Communication Compression and Bernoulli Aggregation. CoRR abs/2206.03588 (2022) - [i4]Maksim Makarenko, Elnur Gasanov, Rustem Islamov, Abdurakhmon Sadiev, Peter Richtárik:
Adaptive Compression for Communication-Efficient Distributed Training. CoRR abs/2211.00188 (2022) - 2021
- [c1]Rustem Islamov, Xun Qian, Peter Richtárik:
Distributed Second Order Methods with Fast Rates and Compressed Communication. ICML 2021: 4617-4628 - [i3]Rustem Islamov
Distributed Second Order Methods with Fast Rates and Compressed Communication. CoRR abs/2102.07158 (2021) - [i2]Mher Safaryan
FedNL: Making Newton-Type Methods Applicable to Federated Learning. CoRR abs/2106.02969 (2021) - [i1]Xun Qian
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning. CoRR abs/2111.01847 (2021)
Coauthor Index
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