Stochastic Weakly Convex Optimization Under Heavy-Tailed Noises
Fuente:
arXiv
Saved in:
| Main Authors: | Zhu, Tianxi, Xu, Yi, Ji, Xiangyang |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Near-Optimal Decentralized Stochastic Nonconvex Optimization with Heavy-Tailed Noise
by: Wang, Menglian, et al.
Published: (2026)
by: Wang, Menglian, et al.
Published: (2026)
Optimal Asynchronous Stochastic Nonconvex Optimization under Heavy-Tailed Noise
by: Wu, Yidong, et al.
Published: (2026)
by: Wu, Yidong, et al.
Published: (2026)
Concentration of General Stochastic Approximation Under Heavy-Tailed Markovian Noise
by: Agrawal, Shubhada, et al.
Published: (2026)
by: Agrawal, Shubhada, et al.
Published: (2026)
High Probability Complexity Bounds for Non-Smooth Stochastic Optimization with Heavy-Tailed Noise
by: Gorbunov, Eduard, et al.
Published: (2021)
by: Gorbunov, Eduard, et al.
Published: (2021)
Sign-Based Optimizers Are Effective Under Heavy-Tailed Noise
by: Yu, Dingzhi, et al.
Published: (2026)
by: Yu, Dingzhi, et al.
Published: (2026)
Clipped Gradient Methods for Nonsmooth Convex Optimization under Heavy-Tailed Noise: A Refined Analysis
by: Liu, Zijian
Published: (2025)
by: Liu, Zijian
Published: (2025)
Convergence of Clipped-SGD for Convex $(L_0,L_1)$-Smooth Optimization with Heavy-Tailed Noise
by: Chezhegov, Savelii, et al.
Published: (2025)
by: Chezhegov, Savelii, et al.
Published: (2025)
Sign Operator for Coping with Heavy-Tailed Noise in Non-Convex Optimization: High Probability Bounds Under $(L_0, L_1)$-Smoothness
by: Kornilov, Nikita, et al.
Published: (2025)
by: Kornilov, Nikita, et al.
Published: (2025)
Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping
by: Liu, Zijian, et al.
Published: (2024)
by: Liu, Zijian, et al.
Published: (2024)
In-Expectation Convergence of Stochastic Gradient Methods under Heavy-Tailed Noise
by: Liu, Zijian
Published: (2026)
by: Liu, Zijian
Published: (2026)
Algorithmic Stability of Stochastic Gradient Descent with Momentum under Heavy-Tailed Noise
by: Dang, Thanh, et al.
Published: (2025)
by: Dang, Thanh, et al.
Published: (2025)
Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise
by: Hu, Jun, et al.
Published: (2025)
by: Hu, Jun, et al.
Published: (2025)
Online Convex Optimization with Heavy Tails: Old Algorithms, New Regrets, and Applications
by: Liu, Zijian
Published: (2025)
by: Liu, Zijian
Published: (2025)
Stochastic Weakly Convex Optimization Beyond Lipschitz Continuity
by: Gao, Wenzhi, et al.
Published: (2024)
by: Gao, Wenzhi, et al.
Published: (2024)
Can SGD Handle Heavy-Tailed Noise?
by: Fatkhullin, Ilyas, et al.
Published: (2025)
by: Fatkhullin, Ilyas, et al.
Published: (2025)
High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise
by: Gorbunov, Eduard, et al.
Published: (2023)
by: Gorbunov, Eduard, et al.
Published: (2023)
Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems
by: Puchkin, Nikita, et al.
Published: (2023)
by: Puchkin, Nikita, et al.
Published: (2023)
Scale-Invariant Neural Network Optimization: Norm Geometry and Heavy-Tailed Noise
by: Zhang, Jiayu, et al.
Published: (2026)
by: Zhang, Jiayu, et al.
Published: (2026)
Heavy-Tailed and Long-Range Dependent Noise in Stochastic Approximation: A Finite-Time Analysis
by: Chandak, Siddharth, et al.
Published: (2026)
by: Chandak, Siddharth, et al.
Published: (2026)
Boosting-Enabled Robust System Identification of Partially Observed LTI Systems Under Heavy-Tailed Noise
by: Kanakeri, Vinay, et al.
Published: (2025)
by: Kanakeri, Vinay, et al.
Published: (2025)
Stochastic Zeroth-Order Optimization Under Heavy-Tailed Noise
by: Bakkali, Taha El, et al.
Published: (2026)
by: Bakkali, Taha El, et al.
Published: (2026)
Second-order Optimization under Heavy-Tailed Noise: Hessian Clipping and Sample Complexity Limits
by: Sadiev, Abdurakhmon, et al.
Published: (2025)
by: Sadiev, Abdurakhmon, et al.
Published: (2025)
Convergence Analysis of the PAGE Stochastic Algorithm for Weakly Convex Finite-Sum Optimization
by: Condat, Laurent, et al.
Published: (2025)
by: Condat, Laurent, et al.
Published: (2025)
Muon with Nesterov Momentum: Heavy-Tailed Noise and (Randomized) Inexact Polar Decomposition
by: Choudhury, Sayantan, et al.
Published: (2026)
by: Choudhury, Sayantan, et al.
Published: (2026)
Heavy-Tail Phenomenon in Decentralized SGD
by: Gurbuzbalaban, Mert, et al.
Published: (2022)
by: Gurbuzbalaban, Mert, et al.
Published: (2022)
(Accelerated) Noise-adaptive Stochastic Heavy-Ball Momentum
by: Dang, Anh, et al.
Published: (2024)
by: Dang, Anh, 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)
Stochastic Difference-of-Convex Optimization with Momentum
by: Chayti, El Mahdi, et al.
Published: (2025)
by: Chayti, El Mahdi, et al.
Published: (2025)
The Price of Adaptivity in Stochastic Convex Optimization
by: Carmon, Yair, et al.
Published: (2024)
by: Carmon, Yair, et al.
Published: (2024)
Sharp High-Probability Rates for Nonlinear SGD under Heavy-Tailed Noise via Symmetrization
by: Armacki, Aleksandar, et al.
Published: (2025)
by: Armacki, Aleksandar, et al.
Published: (2025)
Muon Converges under Heavy-Tailed Noise: Nonconvex Hölder-Smooth Empirical Risk Minimization
by: Iiduka, Hideaki
Published: (2026)
by: Iiduka, Hideaki
Published: (2026)
Distributed Stochastic Optimization under Heavy-Tailed Noises
by: Sun, Chao, et al.
Published: (2023)
by: Sun, Chao, et al.
Published: (2023)
Optimal Rates for Robust Stochastic Convex Optimization
by: Gao, Changyu, et al.
Published: (2024)
by: Gao, Changyu, et al.
Published: (2024)
Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions
by: Hu, Quanqi, et al.
Published: (2024)
by: Hu, Quanqi, et al.
Published: (2024)
Tight Long-Term Tail Decay of (Clipped) SGD in Non-Convex Optimization
by: Armacki, Aleksandar, et al.
Published: (2026)
by: Armacki, Aleksandar, et al.
Published: (2026)
Revisiting Gradient Normalization and Clipping for Nonconvex SGD under Heavy-Tailed Noise: Necessity, Sufficiency, and Acceleration
by: Sun, Tao, et al.
Published: (2024)
by: Sun, Tao, et al.
Published: (2024)
Why is Normalization Preferred? A Worst-Case Complexity Theory for Stochastically Preconditioned SGD under Heavy-Tailed Noise
by: Fang, Yuchen, et al.
Published: (2026)
by: Fang, Yuchen, et al.
Published: (2026)
Outlier-Robust Linear System Identification Under Heavy-tailed Noise
by: Kanakeri, Vinay, et al.
Published: (2024)
by: Kanakeri, Vinay, et al.
Published: (2024)
High Probability Bounds for Stochastic Subgradient Schemes with Heavy Tailed Noise
by: Parletta, Daniela A., et al.
Published: (2022)
by: Parletta, Daniela A., et al.
Published: (2022)
High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise
by: Armacki, Aleksandar, et al.
Published: (2023)
by: Armacki, Aleksandar, et al.
Published: (2023)
Similar Items
-
Near-Optimal Decentralized Stochastic Nonconvex Optimization with Heavy-Tailed Noise
by: Wang, Menglian, et al.
Published: (2026) -
Optimal Asynchronous Stochastic Nonconvex Optimization under Heavy-Tailed Noise
by: Wu, Yidong, et al.
Published: (2026) -
Concentration of General Stochastic Approximation Under Heavy-Tailed Markovian Noise
by: Agrawal, Shubhada, et al.
Published: (2026) -
High Probability Complexity Bounds for Non-Smooth Stochastic Optimization with Heavy-Tailed Noise
by: Gorbunov, Eduard, et al.
Published: (2021) -
Sign-Based Optimizers Are Effective Under Heavy-Tailed Noise
by: Yu, Dingzhi, et al.
Published: (2026)