A Single-Loop Gradient Descent and Perturbed Ascent Algorithm for Nonconvex Functional Constrained Optimization
Fuente:
arXiv
Saved in:
| Main Author: | Lu, Songtao |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Min-Max Optimisation for Nonconvex-Nonconcave Functions Using a Random Zeroth-Order Extragradient Algorithm
by: Farzin, Amir Ali, et al.
Published: (2025)
by: Farzin, Amir Ali, et al.
Published: (2025)
Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization
by: Huang, Feihu, et al.
Published: (2023)
by: Huang, Feihu, et al.
Published: (2023)
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)
Super Gradient Descent: Global Optimization requires Global Gradient
by: Achour, Seifeddine
Published: (2024)
by: Achour, Seifeddine
Published: (2024)
Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization
by: Lin, Tianyi, et al.
Published: (2024)
by: Lin, Tianyi, et al.
Published: (2024)
PowerStep: Memory-Efficient Adaptive Optimization via $\ell_p$-Norm Steepest Descent
by: Lu, Yao, et al.
Published: (2026)
by: Lu, Yao, et al.
Published: (2026)
Adaptive Lipschitz-Free Conditional Gradient Methods for Stochastic Composite Nonconvex Optimization
by: Yuan, Ganzhao
Published: (2026)
by: Yuan, Ganzhao
Published: (2026)
Gradient Descent as a Perceptron Algorithm: Understanding Dynamics and Implicit Acceleration
by: Tyurin, Alexander
Published: (2025)
by: Tyurin, Alexander
Published: (2025)
Gradient is All You Need? How Consensus-Based Optimization can be Interpreted as a Stochastic Relaxation of Gradient Descent
by: Riedl, Konstantin, et al.
Published: (2023)
by: Riedl, Konstantin, et al.
Published: (2023)
Provably Faster Gradient Descent via Long Steps
by: Grimmer, Benjamin
Published: (2023)
by: Grimmer, Benjamin
Published: (2023)
On the Convergence of the Gradient Descent Method with Stochastic Fixed-point Rounding Errors under the Polyak-Lojasiewicz Inequality
by: Xia, Lu, et al.
Published: (2023)
by: Xia, Lu, et al.
Published: (2023)
On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems
by: Lin, Tianyi, et al.
Published: (2019)
by: Lin, Tianyi, et al.
Published: (2019)
Minimisation of Quasar-Convex Functions Using Random Zeroth-Order Oracles
by: Farzin, Amir Ali, et al.
Published: (2025)
by: Farzin, Amir Ali, et al.
Published: (2025)
Primal-Dual Methods for Nonsmooth Nonconvex Optimization with Orthogonality Constraints
by: Zhu, Linglingzhi, et al.
Published: (2026)
by: Zhu, Linglingzhi, et al.
Published: (2026)
PRISM: Distribution-free Adaptive Computation of Matrix Functions for Accelerating Neural Network Training
by: Yang, Shenghao, et al.
Published: (2026)
by: Yang, Shenghao, et al.
Published: (2026)
Curvature-Aware Optimization for High-Accuracy Physics-Informed Neural Networks
by: Jnini, Anas, et al.
Published: (2026)
by: Jnini, Anas, et al.
Published: (2026)
Fast and Provable Tensor-Train Format Tensor Completion via Precondtioned Riemannian Gradient Descent
by: Bian, Fengmiao, et al.
Published: (2025)
by: Bian, Fengmiao, et al.
Published: (2025)
Dual Cone Gradient Descent for Training Physics-Informed Neural Networks
by: Hwang, Youngsik, et al.
Published: (2024)
by: Hwang, Youngsik, et al.
Published: (2024)
Modified Loss of Momentum Gradient Descent: Fine-Grained Analysis
by: Cattaneo, Matias D., et al.
Published: (2025)
by: Cattaneo, Matias D., et al.
Published: (2025)
A Block Coordinate Descent Method for Nonsmooth Composite Optimization under Orthogonality Constraints
by: Yuan, Ganzhao
Published: (2023)
by: Yuan, Ganzhao
Published: (2023)
A second-order method landing on the Stiefel manifold via Newton$\unicode{x2013}$Schulz iteration
by: Xiong, Xinhui, et al.
Published: (2026)
by: Xiong, Xinhui, et al.
Published: (2026)
Examining Policy Entropy of Reinforcement Learning Agents for Personalization Tasks
by: Dereventsov, Anton, et al.
Published: (2022)
by: Dereventsov, Anton, et al.
Published: (2022)
Transformers Can Implement Preconditioned Richardson Iteration for In-Context Gaussian Kernel Regression
by: Yan, Mingsong, et al.
Published: (2026)
by: Yan, Mingsong, et al.
Published: (2026)
Geometric Data Valuation via Leverage Scores
by: Mendoza-Smith, Rodrigo
Published: (2025)
by: Mendoza-Smith, Rodrigo
Published: (2025)
Muon is Not That Special: Random or Inverted Spectra Work Just as Well
by: Shumaylov, Zakhar, et al.
Published: (2026)
by: Shumaylov, Zakhar, et al.
Published: (2026)
Scaling physics-informed hard constraints with mixture-of-experts
by: Chalapathi, Nithin, et al.
Published: (2024)
by: Chalapathi, Nithin, et al.
Published: (2024)
Learning Explicitly Conditioned Sparsifying Transforms
by: Pătraşcu, Andrei, et al.
Published: (2024)
by: Pătraşcu, Andrei, et al.
Published: (2024)
Parametrizing Convex Sets Using Sublinear Neural Networks
by: Martinet, Eloi
Published: (2026)
by: Martinet, Eloi
Published: (2026)
Maximum Principle of Optimal Probability Density Control
by: Gaby, Nathan, et al.
Published: (2025)
by: Gaby, Nathan, et al.
Published: (2025)
Adaptive Proximal Gradient Method for Convex Optimization
by: Malitsky, Yura, et al.
Published: (2023)
by: Malitsky, Yura, et al.
Published: (2023)
Practical Topics in Optimization
by: Lu, Jun
Published: (2025)
by: Lu, Jun
Published: (2025)
Dynamic Proximal Gradient Algorithms for Schatten-$p$ Quasi-Norm Regularized Problems
by: Shen, Weiping, et al.
Published: (2026)
by: Shen, Weiping, et al.
Published: (2026)
Convergent Proximal Multiblock ADMM for Nonconvex Dynamics-Constrained Optimization
by: Li, Bowen, et al.
Published: (2025)
by: Li, Bowen, et al.
Published: (2025)
Convergence Analysis of Fractional Gradient Descent
by: Aggarwal, Ashwani
Published: (2023)
by: Aggarwal, Ashwani
Published: (2023)
ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning
by: Schwencke, Nilo, et al.
Published: (2024)
by: Schwencke, Nilo, et al.
Published: (2024)
Universal Approximation of Nonlinear Operators and Their Derivatives
by: de Feo, Filippo
Published: (2026)
by: de Feo, Filippo
Published: (2026)
Fast Unconstrained Optimization via Hessian Averaging and Adaptive Gradient Sampling Methods
by: O'Leary-Roseberry, Thomas, et al.
Published: (2024)
by: O'Leary-Roseberry, Thomas, et al.
Published: (2024)
Boosting Gradient Ascent for Continuous DR-submodular Maximization
by: Zhang, Qixin, et al.
Published: (2024)
by: Zhang, Qixin, et al.
Published: (2024)
UAdam: Unified Adam-Type Algorithmic Framework for Non-Convex Stochastic Optimization
by: Jiang, Yiming, et al.
Published: (2023)
by: Jiang, Yiming, et al.
Published: (2023)
Faster Randomized Methods for Orthogonality Constrained Problems
by: Shustin, Boris, et al.
Published: (2021)
by: Shustin, Boris, et al.
Published: (2021)
Similar Items
-
Min-Max Optimisation for Nonconvex-Nonconcave Functions Using a Random Zeroth-Order Extragradient Algorithm
by: Farzin, Amir Ali, et al.
Published: (2025) -
Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization
by: Huang, Feihu, et al.
Published: (2023) -
A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems
by: Zhang, Jiawei, et al.
Published: (2020) -
Super Gradient Descent: Global Optimization requires Global Gradient
by: Achour, Seifeddine
Published: (2024) -
Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization
by: Lin, Tianyi, et al.
Published: (2024)