Rustem Islamov

35 papers A* 7A 3Journal 25

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adaptive Methods Are Preferable in High Privacy Settings: An SDE Perspective. CoRR Enea Monzio Compagnoni, Alessandro Stanghellini, Rustem Islamov, Aurélien Lucchi, Anastasiia Koloskova
2026	J	`jnl`	Byzantine-Robust and Differentially Private Federated Optimization under Weaker Assumptions. CoRR Rustem Islamov, Grigory Malinovsky, Alexander Gaponov, Aurélien Lucchi, Peter Richtárik, Eduard Gorbunov
2026	J	`jnl`	Non-Euclidean Gradient Descent Operates at the Edge of Stability. CoRR Rustem Islamov, Michael Crawshaw, Jeremy Cohen, Robert M. Gower
2026	J	`jnl`	On the Role of Batch Size in Stochastic Conditional Gradient Methods. CoRR Rustem Islamov, Roman Machacek, Aurélien Lucchi, Antonio Silveti-Falls, Eduard Gorbunov, Volkan Cevher
2025	A*	`conf`	Adaptive Methods through the Lens of SDEs: Theoretical Insights on the Role of Noise. ICLR Enea Monzio Compagnoni, Tianlin Liu, Rustem Islamov, Frank Norbert Proske, Antonio Orvieto, Aurélien Lucchi
2025	J	`jnl`	Double Momentum and Error Feedback for Clipping with Fast Rates and Differential Privacy. CoRR Rustem Islamov, Samuel Horváth, Aurélien Lucchi, Peter Richtárik, Eduard Gorbunov
2025	J	`jnl`	Enhancing Optimizer Stability: Momentum Adaptation of The NGN Step-size. CoRR Rustem Islamov, Niccolò Ajroldi, Antonio Orvieto, Aurélien Lucchi
2025	J	`jnl`	On the Interaction of Noise, Compression Role, and Adaptivity under (L CoRR Enea Monzio Compagnoni, Rustem Islamov, Antonio Orvieto, Eduard Gorbunov
2025	J	`jnl`	Partially Personalized Federated Learning: Breaking the Curse of Data Heterogeneity. Trans. Mach. Learn. Res. Konstantin Mishchenko, Rustem Islamov, Eduard Gorbunov, Samuel Horváth
2025	A*	`conf`	Safe-EF: Error Feedback for Non-smooth Constrained Optimization. ICML Rustem Islamov, Yarden As, Ilyas Fatkhullin
2025	J	`jnl`	Safe-EF: Error Feedback for Nonsmooth Constrained Optimization. CoRR Rustem Islamov, Yarden As, Ilyas Fatkhullin
2025	A*	`conf`	Towards Faster Decentralized Stochastic Optimization with Communication Compression. ICLR Rustem Islamov, Yuan Gao, Sebastian U. Stich
2025	A	`conf`	Unbiased and Sign Compression in Distributed Learning: Comparing Noise Resilience via SDEs. AISTATS Enea Monzio Compagnoni, Rustem Islamov, Frank Norbert Proske, Aurélien Lucchi
2025	J	`jnl`	Unbiased and Sign Compression in Distributed Learning: Comparing Noise Resilience via SDEs. CoRR Enea Monzio Compagnoni, Rustem Islamov, Frank Norbert Proske, Aurélien Lucchi
2025	J	`jnl`	Why Do We Need Warm-up? A Theoretical Perspective. CoRR Foivos Alimisis, Rustem Islamov, Aurélien Lucchi
2024	J	`jnl`	Adaptive Methods through the Lens of SDEs: Theoretical Insights on the Role of Noise. CoRR Enea Monzio Compagnoni, Tianlin Liu, Rustem Islamov, Frank Norbert Proske, Antonio Orvieto, Aurélien Lucchi
2024	A	`conf`	AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms. AISTATS Rustem Islamov, Mher Safaryan, Dan Alistarh
2024	A*	`conf`	EControl: Fast Distributed Optimization with Compression and Error Control. ICLR Yuan Gao, Rustem Islamov, Sebastian U. Stich
2024	A*	`conf`	Loss Landscape Characterization of Neural Networks without Over-Parametrization. NeurIPS Rustem Islamov, Niccolò Ajroldi, Antonio Orvieto, Aurélien Lucchi
2024	J	`jnl`	Loss Landscape Characterization of Neural Networks without Over-Parametrization. CoRR Rustem Islamov, Niccolò Ajroldi, Antonio Orvieto, Aurélien Lucchi
2024	J	`jnl`	Near Optimal Decentralized Optimization with Compression and Momentum Tracking. CoRR Rustem Islamov, Yuan Gao, Sebastian U. Stich
2023	J	`jnl`	Adaptive Compression for Communication-Efficient Distributed Training. Trans. Mach. Learn. Res. Maksim Makarenko, Elnur Gasanov, Abdurakhmon Sadiev, Rustem Islamov, Peter Richtárik
2023	J	`jnl`	AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms. CoRR Rustem Islamov, Mher Safaryan, Dan Alistarh
2023	J	`jnl`	Clip21: Error Feedback for Gradient Clipping. CoRR Sarit Khirirat, Eduard Gorbunov, Samuel Horváth, Rustem Islamov, Fakhri Karray, Peter Richtárik
2023	J	`jnl`	Distributed Newton-Type Methods with Communication Compression and Bernoulli Aggregation. Trans. Mach. Learn. Res. Rustem Islamov, Xun Qian, Slavomír Hanzely, Mher Safaryan, Peter Richtárik
2023	J	`jnl`	EControl: Fast Distributed Optimization with Compression and Error Control. CoRR Yuan Gao, Rustem Islamov, Sebastian U. Stich
2023	J	`jnl`	Partially Personalized Federated Learning: Breaking the Curse of Data Heterogeneity. CoRR Konstantin Mishchenko, Rustem Islamov, Eduard Gorbunov, Samuel Horváth
2022	J	`jnl`	Adaptive Compression for Communication-Efficient Distributed Training. CoRR Maksim Makarenko, Elnur Gasanov, Rustem Islamov, Abdurakhmon Sadiev, Peter Richtárik
2022	A	`conf`	Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning. AISTATS Xun Qian, Rustem Islamov, Mher Safaryan, Peter Richtárik
2022	J	`jnl`	Distributed Newton-Type Methods with Communication Compression and Bernoulli Aggregation. CoRR Rustem Islamov, Xun Qian, Slavomír Hanzely, Mher Safaryan, Peter Richtárik
2022	A*	`conf`	FedNL: Making Newton-Type Methods Applicable to Federated Learning. ICML Mher Safaryan, Rustem Islamov, Xun Qian, Peter Richtárik
2021	J	`jnl`	Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning. CoRR Xun Qian, Rustem Islamov, Mher Safaryan, Peter Richtárik
2021	A*	`conf`	Distributed Second Order Methods with Fast Rates and Compressed Communication. ICML Rustem Islamov, Xun Qian, Peter Richtárik
2021	J	`jnl`	Distributed Second Order Methods with Fast Rates and Compressed Communication. CoRR Rustem Islamov, Xun Qian, Peter Richtárik
2021	J	`jnl`	FedNL: Making Newton-Type Methods Applicable to Federated Learning. CoRR Mher Safaryan, Rustem Islamov, Xun Qian, Peter Richtárik