Cover Image

Fully Adaptive Zeroth-Order Method for Minimizing Functions with Compressible Gradients

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Grapiglia, Geovani Nunes, McKenzie, Daniel
Format:	Preprint
Published:	2025
Subjects:	Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Non-Monotone Line-Search Method for Minimizing Functions with Spurious Local Minima
by: Aminifard, Zohreh, et al.
Published: (2025)

On the Complexity of Lower-Order Implementations of Higher-Order Methods
by: Doikov, Nikita, et al.
Published: (2025)

A Finite-Difference Trust-Region Method for Convexly Constrained Smooth Optimization
by: Davar, Dânâ, et al.
Published: (2025)

TRFD: A derivative-free trust-region method based on finite differences for composite nonsmooth optimization
by: Davar, Dânâ, et al.
Published: (2024)

Universal nonmonotone line search method for nonconvex multiobjective optimization problems with convex constraints
by: Pinheiro, Maria Eduarda, et al.
Published: (2024)

Enhancing finite-difference based derivative-free optimization methods with machine learning
by: Taminiau, Timothé, et al.
Published: (2025)

Riemannian optimization with finite-difference gradient approximations
by: Taminiau, Timothé, et al.
Published: (2026)

Complexity of quadratic penalty methods with adaptive accuracy under a PL condition for the constraints
by: Goyens, Florentin, et al.
Published: (2026)

Sub-sampled Trust-Region Methods with Deterministic Worst-Case Complexity Guarantees
by: Goncalves, Max L. N., et al.
Published: (2025)

A Riemannian AdaGrad-Norm Method
by: Bento, Glaydston de C., et al.
Published: (2025)

Active-set Newton-MR methods for nonconvex optimization problems with bound constraints
by: Birgin, Ernesto G., et al.
Published: (2025)

A Zeroth-Order Extra-Gradient Method for Black-Box Constrained Optimization
by: Zhou, Yuke, et al.
Published: (2025)

High-Probability Guarantees for Random Zeroth-Order Gradient Descent on Smooth Functions
by: Ye, Haishan
Published: (2026)

On Adaptivity in Zeroth-Order Optimization
by: Dbouk, Hassan, et al.
Published: (2026)

Compressed Zeroth-Order Algorithm for Stochastic Distributed Nonconvex Optimization
by: Wang, Haonan, et al.
Published: (2025)

Heterogeneous Distributed Zeroth-Order Nonconvex Optimization with Communication Compression
by: Wang, Haonan, et al.
Published: (2026)

On the Resolution of Stochastic MPECs over Networks: Distributed Implicit Zeroth-Order Gradient Tracking Methods
by: Ebrahimi, Mohammadjavad, et al.
Published: (2025)

Why Does Adaptive Zeroth-Order Optimization Work?
by: Ye, Haishan, et al.
Published: (2026)

Fully Zeroth-Order Bilevel Programming via Gaussian Smoothing
by: Aghasi, Alireza, et al.
Published: (2024)

High-Probability Guarantees for Random Zeroth-Order (Stochastic) Gradient Descent
by: Ye, Haishan
Published: (2026)

Distributed Zeroth-Order Optimization with Rademacher Perturbations and Momentum Gradient Tracking
by: Su, Yanxu, et al.
Published: (2026)

Distributed Stochastic Zeroth-Order Optimization with Compressed Communication
by: Hua, Youqing, et al.
Published: (2025)

On the Inherent Privacy of Zeroth Order Projected Gradient Descent
by: Gupta, Devansh, et al.
Published: (2025)

Accelerating Single-Point Zeroth-Order Optimization with Regression-Based Gradient Surrogates
by: Chen, Xin, et al.
Published: (2025)

Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity
by: de Vazelhes, William, et al.
Published: (2022)

Variance-Reduced Gradient Estimator for Nonconvex Zeroth-Order Distributed Optimization
by: Mu, Huaiyi, et al.
Published: (2024)

Compressed Momentum-based Single-Point Zeroth-Order Algorithm for Stochastic Distributed Nonconvex Optimization
by: Chen, Linjing, et al.
Published: (2025)

Optimal Zeroth-Order Bilevel Optimization
by: Aghasi, Alireza, et al.
Published: (2025)

Zeroth-order Gradient and Quasi-Newton Methods for Nonsmooth Nonconvex Stochastic Optimization
by: Marrinan, Luke, et al.
Published: (2023)

Zeroth-Order Federated Methods for Stochastic MPECs and Nondifferentiable Nonconvex Hierarchical Optimization
by: Qiu, Yuyang, et al.
Published: (2023)

Zeroth-Order Katyusha: An Accelerated Derivative-Free Method for Composite Convex Optimization
by: Zhang, Silan, et al.
Published: (2024)

LORENZA: Enhancing Generalization in Low-Rank Gradient LLM Training via Efficient Zeroth-Order Adaptive SAM
by: Refael, Yehonathan, et al.
Published: (2025)

A Zeroth-order Proximal Stochastic Gradient Method for Weakly Convex Stochastic Optimization
by: Pougkakiotis, Spyridon, et al.
Published: (2022)

On Solving Minimization and Min-Max Problems by First-Order Methods with Relative Error in Gradients
by: Vasin, Artem, et al.
Published: (2025)

First- and Zeroth-Order Learning in Asynchronous Games
by: Wang, Zifan, et al.
Published: (2025)

Nonsmooth Optimization with Zeroth Order Comparison Feedback
by: Bakkali, Taha El, et al.
Published: (2026)

Zeroth-Order Methods for Stochastic Nonconvex Nonsmooth Composite Optimization
by: Chen, Ziyi, et al.
Published: (2025)

Stochastic Zeroth-Order Method for Computing Generalized Rayleigh Quotients
by: Bresch, Jonas, et al.
Published: (2025)

On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
by: Ma, Shaocong, et al.
Published: (2025)

Riemannian Zeroth-Order Gradient Estimation with Structure-Preserving Metrics for Geodesically Incomplete Manifolds
by: Ma, Shaocong, et al.
Published: (2026)