Copertina

Doubly Smoothed Optimistic Gradients: A Universal Approach for Smooth Minimax Problems

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zheng, Taoli, So, Anthony Man-Cho, Li, Jiajin
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Optimization and Control
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Set Smoothness Unlocks Clarke Hyper-stationarity in Bilevel Optimization
di: Chen, He, et al.
Pubblicazione: (2025)

Efficient Single-Loop Stochastic Algorithms for Nonconvex-Concave Minimax Optimization
di: Jiang, Xia, et al.
Pubblicazione: (2025)

Shuffling Gradient Descent-Ascent with Variance Reduction for Nonconvex-Strongly Concave Smooth Minimax Problems
di: Jiang, Xia, et al.
Pubblicazione: (2024)

Nonsmooth Nonconvex-Nonconcave Minimax Optimization: Primal-Dual Balancing and Iteration Complexity Analysis
di: Li, Jiajin, et al.
Pubblicazione: (2022)

Smoothing Meets Perturbation: Unified and Tight Analysis for Nonconvex-Concave Minimax Optimization
di: Li, Jiajin, et al.
Pubblicazione: (2026)

A Riemannian Alternating Descent Ascent Algorithmic Framework for Nonconvex-Linear Minimax Problems on Riemannian Manifolds
di: Xu, Meng, et al.
Pubblicazione: (2024)

Spurious Stationarity and Hardness Results for Bregman Proximal-Type Algorithms
di: Chen, He, et al.
Pubblicazione: (2024)

Moving Anchor Extragradient Methods For Smooth Structured Minimax Problems
di: Alcala, James K., et al.
Pubblicazione: (2023)

Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization
di: Shen, Wei, et al.
Pubblicazione: (2023)

An Optimistic Gradient Tracking Method for Distributed Minimax Optimization
di: Huang, Yan, et al.
Pubblicazione: (2025)

Natural Policy Gradient as Doubly Smoothed Policy Iteration: A Bellman-Operator Framework
di: Nanda, Phalguni, et al.
Pubblicazione: (2026)

Testing Approximate Stationarity Concepts for Piecewise Affine Functions
di: Tian, Lai, et al.
Pubblicazione: (2025)

On the Oracle Complexity of a Riemannian Inexact Augmented Lagrangian Method for Riemannian Nonsmooth Composite Problems
di: Xu, Meng, et al.
Pubblicazione: (2024)

Improved Performance of Stochastic Gradients with Gaussian Smoothing
di: Starnes, Andrew, et al.
Pubblicazione: (2023)

Gradient Descent for Convex and Smooth Noisy Optimization
di: Hu, Feifei, et al.
Pubblicazione: (2024)

$\ell_1$-norm rank-one symmetric matrix factorization has no spurious second-order stationary points
di: Guan, Jiewen, et al.
Pubblicazione: (2024)

On subdifferential chain rule of matrix factorization and beyond
di: Guan, Jiewen, et al.
Pubblicazione: (2024)

Accelerated Price Adjustment for Fisher Markets with Exact Recovery of Competitive Equilibrium
di: Chen, He, et al.
Pubblicazione: (2025)

Computing Competitive Equilibrium for Chores: Linear Convergence and Lightweight Iteration
di: Chen, He, et al.
Pubblicazione: (2024)

Inertial Bregman Proximal Gradient under Partial Smoothness
di: Godeme, Jean-Jacques
Pubblicazione: (2025)

Adaptive Accelerated Gradient Method for Smooth Convex Optimization
di: Wang, Zepeng, et al.
Pubblicazione: (2025)

Decentralized Relaxed Smooth Optimization with Gradient Descent Methods
di: Jiang, Zhanhong, et al.
Pubblicazione: (2025)

Nonlinearly Preconditioned Gradient Methods under Generalized Smoothness
di: Oikonomidis, Konstantinos, et al.
Pubblicazione: (2025)

Clipped Stochastic Gradient Tracking For Locally Smooth Functions
di: Mei, Leilei, et al.
Pubblicazione: (2026)

Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization
di: Jiang, Ruichen, et al.
Pubblicazione: (2024)

Variable Smoothing Alternating Proximal Gradient Algorithm for Coupled Composite Optimization
di: Long, Xian-Jun, et al.
Pubblicazione: (2025)

Information Geometry of Exponentiated Gradient: Convergence beyond L-Smoothness
di: Elshiaty, Yara, et al.
Pubblicazione: (2025)

Inexactly Smooth Performance Estimation and New Optimized Gradient Methods
di: Zoll, Aaron, et al.
Pubblicazione: (2026)

Generalized Stochastic Gradient Descent with Momentum Methods for Smooth Optimization
di: Wang, Zimeng, et al.
Pubblicazione: (2026)

Randomized Block-Coordinate Optimistic Gradient Algorithms for Root-Finding Problems
di: Tran-Dinh, Quoc, et al.
Pubblicazione: (2023)

Lower-level Duality Based Reformulation and Majorization Minimization Algorithm for Hyperparameter Optimization
di: Chen, He, et al.
Pubblicazione: (2024)

Omega: Optimistic EMA Gradients
di: Ramirez, Juan, et al.
Pubblicazione: (2023)

Gradient-Normalized Smoothness for Optimization with Approximate Hessians
di: Semenov, Andrei, et al.
Pubblicazione: (2025)

Directional Smoothness and Gradient Methods: Convergence and Adaptivity
di: Mishkin, Aaron, et al.
Pubblicazione: (2024)

Smoothing Accelerated Proximal Gradient Method with Backtracking for Nonsmooth Multiobjective Optimization
di: Chengzhi, Huang
Pubblicazione: (2025)

Convergence Analysis of Stochastic Accelerated Gradient Methods for Generalized Smooth Optimizations
di: Yu, Chenhao, et al.
Pubblicazione: (2025)

Optimizing $(L_0, L_1)$-Smooth Functions by Gradient Methods
di: Vankov, Daniil, et al.
Pubblicazione: (2024)

Toward a Unified Theory of Gradient Descent under Generalized Smoothness
di: Tyurin, Alexander
Pubblicazione: (2024)

Last-Iterate Complexity of SGD for Convex and Smooth Stochastic Problems
di: Garrigos, Guillaume, et al.
Pubblicazione: (2025)

On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems
di: Lin, Tianyi, et al.
Pubblicazione: (2019)