Saved in:
| Main Authors: | Chervonenkis, Boris, Krasnov, Andrei, Gasnikov, Alexander, Lobanov, Aleksandr |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.11077 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Acceleration Exists! Optimization Problems When Oracle Can Only Compare Objective Function Values
by: Lobanov, Aleksandr, et al.
Published: (2024)
by: Lobanov, Aleksandr, et al.
Published: (2024)
Power of Generalized Smoothness in Stochastic Convex Optimization: First- and Zero-Order Algorithms
by: Lobanov, Aleksandr, et al.
Published: (2025)
by: Lobanov, Aleksandr, et al.
Published: (2025)
Accelerated Zero-Order SGD Method for Solving the Black Box Optimization Problem under "Overparametrization" Condition
by: Lobanov, Aleksandr, et al.
Published: (2023)
by: Lobanov, Aleksandr, et al.
Published: (2023)
The Black-Box Optimization Problem: Zero-Order Accelerated Stochastic Method via Kernel Approximation
by: Lobanov, Aleksandr, et al.
Published: (2023)
by: Lobanov, Aleksandr, et al.
Published: (2023)
Randomized gradient-free methods in convex optimization
by: Gasnikov, Alexander, et al.
Published: (2022)
by: Gasnikov, Alexander, et al.
Published: (2022)
Gradient-free algorithm for saddle point problems under overparametrization
by: Statkevich, Ekaterina, et al.
Published: (2024)
by: Statkevich, Ekaterina, et al.
Published: (2024)
Linear Convergence Rate in Convex Setup is Possible! Gradient Descent Method Variants under $(L_0,L_1)$-Smoothness
by: Lobanov, Aleksandr, et al.
Published: (2024)
by: Lobanov, Aleksandr, et al.
Published: (2024)
About some works of Boris Polyak on convergence of gradient methods and their development
by: Ablaev, Seydamet, et al.
Published: (2023)
by: Ablaev, Seydamet, et al.
Published: (2023)
Improved Iteration Complexity in Black-Box Optimization Problems under Higher Order Smoothness Function Condition
by: Lobanov, Aleksandr
Published: (2024)
by: Lobanov, Aleksandr
Published: (2024)
On quasi-convex smooth optimization problems by a comparison oracle
by: Gasnikov, A. V., et al.
Published: (2024)
by: Gasnikov, A. V., et al.
Published: (2024)
Gradient-Free Approaches is a Key to an Efficient Interaction with Markovian Stochasticity
by: Prokhorov, Boris, et al.
Published: (2026)
by: Prokhorov, Boris, et al.
Published: (2026)
Median Clipping for Zeroth-order Non-Smooth Convex Optimization and Multi-Armed Bandit Problem with Heavy-tailed Symmetric Noise
by: Kornilov, Nikita, et al.
Published: (2024)
by: Kornilov, Nikita, et al.
Published: (2024)
Bregman Proximal Method for Efficient Communications under Similarity
by: Beznosikov, Aleksandr, et al.
Published: (2023)
by: Beznosikov, Aleksandr, et al.
Published: (2023)
Accelerated zero-order SGD under high-order smoothness and overparameterized regime
by: Bychkov, Georgii, et al.
Published: (2024)
by: Bychkov, Georgii, et al.
Published: (2024)
Avoiding Bias in Clipped SGD for Overparameterized Models under Generalized Smoothness
by: Lobanov, Aleksandr, et al.
Published: (2026)
by: Lobanov, Aleksandr, et al.
Published: (2026)
Adaptive Regularized Newton Method with Inexact Hessian
by: Shestakov, Aleksandr, et al.
Published: (2025)
by: Shestakov, Aleksandr, et al.
Published: (2025)
Optimal Analysis of Method with Batching for Monotone Stochastic Finite-Sum Variational Inequalities
by: Pichugin, Alexander, et al.
Published: (2024)
by: Pichugin, Alexander, et al.
Published: (2024)
Exploiting higher-order derivatives in convex optimization methods
by: Kamzolov, Dmitry, et al.
Published: (2022)
by: Kamzolov, Dmitry, et al.
Published: (2022)
Lower and upper bounds of the convergence rate of gradient methods with composite noise in gradient
by: Vasin, Artem, et al.
Published: (2026)
by: Vasin, Artem, et al.
Published: (2026)
Extragradient Sliding for Composite Non-Monotone Variational Inequalities
by: Emelyanov, Roman, et al.
Published: (2024)
by: Emelyanov, Roman, et al.
Published: (2024)
Local SGD for Near-Quadratic Problems: Improving Convergence under Unconstrained Noise Conditions
by: Sadchikov, Andrey, et al.
Published: (2024)
by: Sadchikov, Andrey, et al.
Published: (2024)
Accelerated Methods with Compression for Horizontal and Vertical Federated Learning
by: Stanko, Sergey, et al.
Published: (2024)
by: Stanko, Sergey, et al.
Published: (2024)
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities
by: Beznosikov, Aleksandr, et al.
Published: (2023)
by: Beznosikov, Aleksandr, et al.
Published: (2023)
Method with Batching for Stochastic Finite-Sum Variational Inequalities in Non-Euclidean Setting
by: Pichugin, Alexander, et al.
Published: (2024)
by: Pichugin, Alexander, et al.
Published: (2024)
Stochastic Frank-Wolfe: Unified Analysis and Zoo of Special Cases
by: Nazykov, Ruslan, et al.
Published: (2024)
by: Nazykov, Ruslan, et al.
Published: (2024)
Optimal Data Splitting in Distributed Optimization for Machine Learning
by: Medyakov, Daniil, et al.
Published: (2024)
by: Medyakov, Daniil, et al.
Published: (2024)
Accelerated Stochastic Gradient Method with Applications to Consensus Problem in Markov-Varying Networks
by: Solodkin, Vladimir, et al.
Published: (2024)
by: Solodkin, Vladimir, et al.
Published: (2024)
The Mirror-Prox Sliding Method for Non-smooth decentralized saddle-point problems
by: Kuruzov, Ilya, et al.
Published: (2022)
by: Kuruzov, Ilya, et al.
Published: (2022)
Distributed Saddle-Point Problems: Lower Bounds, Near-Optimal and Robust Algorithms
by: Beznosikov, Aleksandr, et al.
Published: (2020)
by: Beznosikov, Aleksandr, et al.
Published: (2020)
Wall-Clock Complexity for Zeroth-Order Optimization with Tunable Oracle Fidelity
by: Suvorikova, Alexandra, et al.
Published: (2026)
by: Suvorikova, Alexandra, et al.
Published: (2026)
Advancing the lower bounds: An accelerated, stochastic, second-order method with optimal adaptation to inexactness
by: Agafonov, Artem, et al.
Published: (2023)
by: Agafonov, Artem, et al.
Published: (2023)
Universal methods for variational inequalities: deterministic and stochastic cases
by: Klimza, Anton, et al.
Published: (2024)
by: Klimza, Anton, et al.
Published: (2024)
YuriiFormer: A Suite of Nesterov-Accelerated Transformers
by: Zimin, Aleksandr, et al.
Published: (2026)
by: Zimin, Aleksandr, et al.
Published: (2026)
Fractional-Order Nesterov Dynamics for Convex Optimization
by: Ranoto, Tumelo
Published: (2025)
by: Ranoto, Tumelo
Published: (2025)
Decentralized Finite-Sum Optimization over Time-Varying Networks
by: Metelev, Dmitry, et al.
Published: (2024)
by: Metelev, Dmitry, et al.
Published: (2024)
One-Point Feedback for Composite Optimization with Applications to Distributed and Federated Learning
by: Beznosikov, Aleksandr, et al.
Published: (2021)
by: Beznosikov, Aleksandr, et al.
Published: (2021)
An efficient sieving based secant method for sparse optimization problems with least-squares constraints
by: Li, Qian, et al.
Published: (2023)
by: Li, Qian, et al.
Published: (2023)
Stochastic Decentralized Optimization of Non-Smooth Convex and Convex-Concave Problems over Time-Varying Networks
by: Divilkovskiy, Maxim, et al.
Published: (2025)
by: Divilkovskiy, Maxim, et al.
Published: (2025)
Higher Degree Inexact Model for Optimization problems
by: Alkousa, Mohammad, et al.
Published: (2024)
by: Alkousa, Mohammad, et al.
Published: (2024)
Clipping Improves Adam-Norm and AdaGrad-Norm when the Noise Is Heavy-Tailed
by: Chezhegov, Savelii, et al.
Published: (2024)
by: Chezhegov, Savelii, et al.
Published: (2024)
Similar Items
-
Acceleration Exists! Optimization Problems When Oracle Can Only Compare Objective Function Values
by: Lobanov, Aleksandr, et al.
Published: (2024) -
Power of Generalized Smoothness in Stochastic Convex Optimization: First- and Zero-Order Algorithms
by: Lobanov, Aleksandr, et al.
Published: (2025) -
Accelerated Zero-Order SGD Method for Solving the Black Box Optimization Problem under "Overparametrization" Condition
by: Lobanov, Aleksandr, et al.
Published: (2023) -
The Black-Box Optimization Problem: Zero-Order Accelerated Stochastic Method via Kernel Approximation
by: Lobanov, Aleksandr, et al.
Published: (2023) -
Randomized gradient-free methods in convex optimization
by: Gasnikov, Alexander, et al.
Published: (2022)