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55

Clipping Improves Adam-Norm and AdaGrad-Norm when the Noise Is Heavy-Tailed

13 March 2025 by Savelii Chezhegov and others

Machine Learning, Optimization and Control

Linear Convergence Rate in Convex Setup is Possible! Gradient Descent Method Variants under (L_0,L_1)-Smoothness

19 February 2025 by Aleksandr Lobanov and others

Optimization and Control

Double Momentum and Error Feedback for Clipping with Fast Rates and Differential Privacy

17 February 2025 by Rustem Islamov and others

Machine Learning, Optimization and Control

Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad

13 January 2025 by Sayantan Choudhury and others at

Zayed University

Machine Learning, Artificial Intelligence

Low-Resource Machine Translation through the Lens of Personalized Federated Learning

20 December 2024 by Viktor Moskvoretskii and others

Computation and Language, Machine Learning

Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization

3 December 2024 by Yury Demidovich and others

Optimization and Control, Machine Learning

Initialization using Update Approximation is a Silver Bullet for Extremely Efficient Low-Rank Fine-Tuning

29 November 2024 by Kaustubh Ponkshe and others

Computation and Language, Artificial Intelligence

Error Feedback under (L_0,L_1)-Smoothness: Normalization and Momentum

22 October 2024 by Sarit Khirirat and others

Machine Learning

Median Clipping for Zeroth-order Non-Smooth Convex Optimization and Multi-Armed Bandit Problem with Heavy-tailed Symmetric Noise

8 October 2024 by Nikita Kornilov and others

Optimization and Control

Methods for Convex (L_0,L_1)-Smooth Optimization: Clipping, Acceleration, and Adaptivity

23 September 2024 by Eduard Gorbunov and others

Optimization and Control, Machine Learning

High Probability Complexity Bounds for Non-Smooth Stochastic Optimization with Heavy-Tailed Noise

30 August 2024 by Eduard Gorbunov and others at

Zayed University

Optimization and Control, Machine Learning

High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise

24 July 2024 by Eduard Gorbunov and others

Optimization and Control, Machine Learning

Federated Learning Can Find Friends That Are Advantageous

17 July 2024 by Nazarii Tupitsa and others

Machine Learning, Optimization and Control

Byzantine Robustness and Partial Participation Can Be Achieved at Once: Just Clip Gradient Differences

7 June 2024 by Grigory Malinovsky and others

Machine Learning, Artificial Intelligence

Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations

28 May 2024 by Artem Agafonov and others at

Zayed University

Optimization and Control

Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems

17 April 2024 by Nikita Puchkin and others

Optimization and Control, Data Structures and Algorithms

Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates

9 March 2024 by Ahmad Rammal and others

Optimization and Control, Machine Learning

Randomized gradient-free methods in convex optimization

12 February 2024 by Alexander Gasnikov and others

Optimization and Control

Distributed Learning with Compressed Gradient Differences

28 December 2023 by Konstantin Mishchenko and others

Machine Learning, Optimization and Control

Implicitly normalized forecaster with clipping for linear and non-linear heavy-tailed multi-armed bandits

26 December 2023 by Yuriy Dorn and others

Machine Learning, Optimization and Control

Single-Call Stochastic Extragradient Methods for Structured Non-monotone Variational Inequalities: Improved Analysis under Weaker Conditions

12 November 2023 by Sayantan Choudhury and others

Optimization and Control, Computer Science and Game Theory

Byzantine-Tolerant Methods for Distributed Variational Inequalities

8 November 2023 by Nazarii Tupitsa and others

Machine Learning, Optimization and Control

Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance

28 October 2023 by Nikita Kornilov and others

Optimization and Control

Intermediate Gradient Methods with Relative Inexactness

30 September 2023 by Nikita Kornilov and others

Optimization and Control

High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance

18 July 2023 by Abdurakhmon Sadiev and others

Optimization and Control, Machine Learning

Clip21: Error Feedback for Gradient Clipping

30 May 2023 by Sarit Khirirat and others

Machine Learning, Optimization and Control

Partially Personalized Federated Learning: Breaking the Curse of Data Heterogeneity

29 May 2023 by Konstantin Mishchenko and others

Machine Learning, Artificial Intelligence

Unified analysis of SGD-type methods

29 March 2023 by Eduard Gorbunov at

Zayed University

Optimization and Control, Machine Learning

Byzantine-Robust Loopless Stochastic Variance-Reduced Gradient

8 March 2023 by Nikita Fedin and Eduard Gorbunov

Optimization and Control, Machine Learning

Convergence of Proximal Point and Extragradient-Based Methods Beyond Monotonicity: the Case of Negative Comonotonicity

7 November 2022 by Eduard Gorbunov and others

Optimization and Control

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Optimization and Control Machine Learning Distributed, Parallel, and Cluster Computing Artificial Intelligence Data Structures and Algorithms Computer Science and Game Theory Computational Complexity Statistics Theory Probability Numerical Analysis