More Optimal Fractional-Order Stochastic Gradient Descent for Non-Convex Optimization Problems
Fuente:
arXiv
Saved in:
| Main Authors: | Partohaghighi, Mohammad, Marcia, Roummel, Chen, YangQuan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Effective Dimension Aware Fractional-Order Stochastic Gradient Descent for Convex Optimization Problems
by: Partohaghighi, Mohammad, et al.
Published: (2025)
by: Partohaghighi, Mohammad, et al.
Published: (2025)
Fractional-Order Federated Learning
by: Partohaghighi, Mohammad, et al.
Published: (2026)
by: Partohaghighi, Mohammad, et al.
Published: (2026)
Fractional Order Federated Learning for Battery Electric Vehicle Energy Consumption Modeling
by: Partohaghighi, Mohammad, et al.
Published: (2026)
by: Partohaghighi, Mohammad, et al.
Published: (2026)
When Gradient Clipping Becomes a Control Mechanism for Differential Privacy in Deep Learning
by: Partohaghighi, Mohammad, et al.
Published: (2026)
by: Partohaghighi, Mohammad, et al.
Published: (2026)
Deep Learning under Fractional-Order Differential Privacy
by: Partohaghighi, Mohammad, et al.
Published: (2026)
by: Partohaghighi, Mohammad, et al.
Published: (2026)
The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
by: Livni, Roi
Published: (2024)
by: Livni, Roi
Published: (2024)
Statistical Roughness-Informed Machine Unlearning
by: Partohaghighi, Mohammad, et al.
Published: (2026)
by: Partohaghighi, Mohammad, et al.
Published: (2026)
Roughness-Informed Federated Learning
by: Partohaghighi, Mohammad, et al.
Published: (2026)
by: Partohaghighi, Mohammad, et al.
Published: (2026)
Rapid Overfitting of Multi-Pass Stochastic Gradient Descent in Stochastic Convex Optimization
by: Vansover-Hager, Shira, et al.
Published: (2025)
by: Vansover-Hager, Shira, et al.
Published: (2025)
Stochastic Non-Smooth Convex Optimization with Unbounded Gradients
by: Kovalev, Dmitry
Published: (2026)
by: Kovalev, Dmitry
Published: (2026)
Enhancing Fractional Gradient Descent with Learned Optimizers
by: Sobotka, Jan, et al.
Published: (2025)
by: Sobotka, Jan, et al.
Published: (2025)
Quantitative Convergence Analysis of Projected Stochastic Gradient Descent for Non-Convex Losses via the Goldstein Subdifferential
by: Zheng, Yuping, et al.
Published: (2025)
by: Zheng, Yuping, et al.
Published: (2025)
Bayesian Optimization for Non-Convex Two-Stage Stochastic Optimization Problems
by: Buckingham, Jack M., et al.
Published: (2024)
by: Buckingham, Jack M., et al.
Published: (2024)
Stochastic Adaptive Gradient Descent Without Descent
by: Aujol, Jean-François, et al.
Published: (2025)
by: Aujol, Jean-François, et al.
Published: (2025)
Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent
by: Vaswani, Sharan, et al.
Published: (2021)
by: Vaswani, Sharan, et al.
Published: (2021)
Decentralized Stochastic Gradient Descent Ascent for Finite-Sum Minimax Problems
by: Gao, Hongchang
Published: (2022)
by: Gao, Hongchang
Published: (2022)
First and Second Order Approximations to Stochastic Gradient Descent Methods with Momentum Terms
by: Lu, Eric
Published: (2025)
by: Lu, Eric
Published: (2025)
Optimal Rates for Robust Stochastic Convex Optimization
by: Gao, Changyu, et al.
Published: (2024)
by: Gao, Changyu, et al.
Published: (2024)
Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
by: Zhang, Liang, et al.
Published: (2023)
by: Zhang, Liang, et al.
Published: (2023)
A Mean-Field Analysis of Neural Stochastic Gradient Descent-Ascent for Functional Minimax Optimization
by: Zhu, Yuchen, et al.
Published: (2024)
by: Zhu, Yuchen, et al.
Published: (2024)
On Penalty-based Bilevel Gradient Descent Method
by: Shen, Han, et al.
Published: (2023)
by: Shen, Han, et al.
Published: (2023)
Convergence Analysis of Stochastic Gradient Descent with MCMC Estimators
by: Li, Tianyou, et al.
Published: (2023)
by: Li, Tianyou, et al.
Published: (2023)
Stochastic Gradient Descent with Strategic Querying
by: Jiang, Nanfei, et al.
Published: (2025)
by: Jiang, Nanfei, et al.
Published: (2025)
Stochastic Gradient Descent with Adaptive Data
by: Che, Ethan, et al.
Published: (2024)
by: Che, Ethan, et al.
Published: (2024)
Probabilistic Guarantees of Stochastic Recursive Gradient in Non-Convex Finite Sum Problems
by: Zhong, Yanjie, et al.
Published: (2024)
by: Zhong, Yanjie, et al.
Published: (2024)
Single Point-Based Distributed Zeroth-Order Optimization with a Non-Convex Stochastic Objective Function
by: Mhanna, Elissa, et al.
Published: (2024)
by: Mhanna, Elissa, et al.
Published: (2024)
Matching the Statistical Query Lower Bound for $k$-Sparse Parity Problems with Sign Stochastic Gradient Descent
by: Kou, Yiwen, et al.
Published: (2024)
by: Kou, Yiwen, et al.
Published: (2024)
Online Non-Stationary Stochastic Quasar-Convex Optimization
by: Pun, Yuen-Man, et al.
Published: (2024)
by: Pun, Yuen-Man, et al.
Published: (2024)
Momentum Does Not Reduce Stochastic Noise in Stochastic Gradient Descent
by: Sato, Naoki, et al.
Published: (2024)
by: Sato, Naoki, et al.
Published: (2024)
Derivatives of Stochastic Gradient Descent in parametric optimization
by: Iutzeler, Franck, et al.
Published: (2024)
by: Iutzeler, Franck, et al.
Published: (2024)
Zeroth-Order Stochastic Mirror Descent Algorithms for Minimax Excess Risk Optimization
by: Gu, Zhihao, et al.
Published: (2024)
by: Gu, Zhihao, et al.
Published: (2024)
SMA-DP: Spectral Memory-Aware Differential Privacy for Deep Learning
by: Partohaghighi, Mohammad, et al.
Published: (2026)
by: Partohaghighi, Mohammad, et al.
Published: (2026)
Using Stochastic Gradient Descent to Smooth Nonconvex Functions: Analysis of Implicit Graduated Optimization
by: Sato, Naoki, et al.
Published: (2023)
by: Sato, Naoki, et al.
Published: (2023)
Nesterov Finds GRAAL: Optimal and Adaptive Gradient Method for Convex Optimization
by: Borodich, Ekaterina, et al.
Published: (2025)
by: Borodich, Ekaterina, et al.
Published: (2025)
On the Inherent Privacy of Zeroth Order Projected Gradient Descent
by: Gupta, Devansh, et al.
Published: (2025)
by: Gupta, Devansh, et al.
Published: (2025)
Gradient Descent, Stochastic Optimization, and Other Tales
by: Lu, Jun
Published: (2022)
by: Lu, Jun
Published: (2022)
A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems
by: Zhang, Jiawei, et al.
Published: (2020)
by: Zhang, Jiawei, et al.
Published: (2020)
Adaptive Step Sizes for Preconditioned Stochastic Gradient Descent
by: Köhne, Frederik, et al.
Published: (2023)
by: Köhne, Frederik, et al.
Published: (2023)
Functional Central Limit Theorem for Stochastic Gradient Descent
by: Flamand, Kessang, et al.
Published: (2026)
by: Flamand, Kessang, et al.
Published: (2026)
Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent
by: Ziyin, Liu, et al.
Published: (2024)
by: Ziyin, Liu, et al.
Published: (2024)
Similar Items
-
Effective Dimension Aware Fractional-Order Stochastic Gradient Descent for Convex Optimization Problems
by: Partohaghighi, Mohammad, et al.
Published: (2025) -
Fractional-Order Federated Learning
by: Partohaghighi, Mohammad, et al.
Published: (2026) -
Fractional Order Federated Learning for Battery Electric Vehicle Energy Consumption Modeling
by: Partohaghighi, Mohammad, et al.
Published: (2026) -
When Gradient Clipping Becomes a Control Mechanism for Differential Privacy in Deep Learning
by: Partohaghighi, Mohammad, et al.
Published: (2026) -
Deep Learning under Fractional-Order Differential Privacy
by: Partohaghighi, Mohammad, et al.
Published: (2026)