Cover Image

A general framework for floating point error analysis of simplex derivatives

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chen, Yiwen, Hare, Warren, Wiebe, Amy
Format:	Preprint
Published:	2024
Subjects:	Numerical Analysis Optimization and Control 65D25, 90C56
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

CLARSTA: A random subspace trust-region algorithm for convex-constrained derivative-free optimization
by: Chen, Yiwen, et al.
Published: (2025)

$Q$-fully Quadratic Modeling and its Application in a Random Subspace Derivative-free Method
by: Chen, Yiwen, et al.
Published: (2023)

Accuracy and Relationships of Quadratic Models in Derivative-free Optimization
by: Chen, Yiwen, et al.
Published: (2026)

Computation of Generalized Derivatives for Abs-Smooth Functions by Backward Mode Algorithmic Differentiation and Implications to Deep Learning
by: Baumgärtner, Lukas, et al.
Published: (2024)

A novel numerical method tailored for unconstrained optimization problems
by: Li, Lin, et al.
Published: (2025)

Convergence analysis of dynamical systems for optimization by an improved Lyapunov framework
by: Tabei, Atsushi, et al.
Published: (2026)

Spectral conjugate gradient projection methods for large-scale monotone equations without Lipschitz continuity
by: Hamiss, Kabenge, et al.
Published: (2026)

ProxiCBO: A Provably Convergent Consensus-Based Method for Composite Optimization
by: Zhang, Haoyu, et al.
Published: (2026)

Swarm-Based Gradient Descent Method for Non-Convex Optimization
by: Lu, Jingcheng, et al.
Published: (2022)

Swarm-based optimization with random descent
by: Tadmor, Eitan, et al.
Published: (2023)

Swarm-based gradient descent meets simulated annealing
by: Ding, Zhiyan, et al.
Published: (2024)

Privacy-Preserving Black-Box Optimization (PBBO): Theory and the Model-Based Algorithm DFOp
by: Xie, Pengcheng
Published: (2025)

Small errors in random zeroth-order optimization are imaginary
by: Jongeneel, Wouter, et al.
Published: (2021)

An accelerated preconditioned proximal gradient algorithm with a generalized Nesterov momentum for PET image reconstruction
by: Lin, Yizun, et al.
Published: (2024)

An interior point method for nonlinear constrained derivative-free optimization
by: Brilli, Andrea, et al.
Published: (2021)

An adaptive framework for first-order gradient methods
by: Hu, Xiaozhe, et al.
Published: (2026)

EnKSGD: A Class Of Preconditioned Black Box Optimization And Inversion Algorithms
by: Irwin, Brian, et al.
Published: (2023)

Randomized subspace correction methods for convex optimization
by: Jiang, Boou, et al.
Published: (2025)

The Global R-linear Convergence of Nesterov's Accelerated Gradient Method with Unknown Strongly Convex Parameter
by: Bao, Chenglong, et al.
Published: (2023)

A practical randomized trust-region method to escape saddle points in high dimension
by: Dragomir, Radu-Alexandru, et al.
Published: (2026)

Accelerated Gradient Methods with Gradient Restart: Global Linear Convergence
by: Bao, Chenglong, et al.
Published: (2024)

A trust-region funnel algorithm for gray-box optimization
by: Hameed, Gul, et al.
Published: (2025)

Kahan's Automatic Step-Size Control for Unconstrained Optimization
by: Meng, Yifeng, et al.
Published: (2025)

On the Global Convergence of Particle Swarm Optimization Methods
by: Huang, Hui, et al.
Published: (2022)

Consensus-Based Optimization Methods Converge Globally
by: Fornasier, Massimo, et al.
Published: (2021)

Convergence of Anisotropic Consensus-Based Optimization in Mean-Field Law
by: Fornasier, Massimo, et al.
Published: (2021)

Gaussian smoothing gradient descent for minimizing functions (GSmoothGD)
by: Starnes, Andrew, et al.
Published: (2023)

A low-rank augmented Lagrangian method for large-scale semidefinite programming based on a hybrid convex-nonconvex approach
by: Monteiro, Renato D. C., et al.
Published: (2024)

Parallel subspace correction methods for semicoercive and nearly semicoercive convex optimization with applications to nonlinear PDEs
by: Lee, Young-Ju, et al.
Published: (2024)

Multiple Scale Methods For Optimization Of Discretized Continuous Functions
by: Richardson, Nicholas J. E., et al.
Published: (2025)

Grassmannian optimization is NP-hard
by: Lai, Zehua, et al.
Published: (2024)

Anderson Accelerated Primal-Dual Hybrid Gradient for solving LP
by: Zhou, Yingxin, et al.
Published: (2025)

Adaptive Multilevel Newton: A Quadratically Convergent Optimization Method
by: Tsipinakis, Nick, et al.
Published: (2025)

A Scale-Shape Dual Newton Method for Entropic Least Squares
by: Barnfield, Nicholas, et al.
Published: (2026)

A Trust Region Proximal Gradient Method for Nonlinear Multi-objective Optimization Problems
by: Ansary, Md Abu Talhamainuddin
Published: (2024)

Approximating Higher-Order Derivative Tensors Using Secant Updates
by: Welzel, Karl, et al.
Published: (2023)

Adaptive Metrics for Norm-Minimization-Based Outer Approximation in Convex Vector Optimization
by: Alshahrani, Mohammed
Published: (2026)

Convergence analysis of a primal-dual optimization-by-continuation algorithm
by: Loris, Ignace, et al.
Published: (2023)

A Two-step Krasnosel'skii-Mann Algorithm with Adaptive Momentum and Its Applications to Image Denoising and Matrix Completion
by: He, Yongxin, et al.
Published: (2025)

Lipschitz minimization and the Goldstein modulus
by: Kong, Siyu, et al.
Published: (2024)