On Global Rates for Regularization Methods based on Secant Derivative Approximations
Fuente:
arXiv
Saved in:
| Main Authors: | Cartis, Coralia, Jerad, Sadok |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Global Convergence of High-Order Regularization Methods with Sums-of-Squares Taylor Models
by: Zhu, Wenqi, et al.
Published: (2024)
by: Zhu, Wenqi, et al.
Published: (2024)
Global Optimality Characterizations and Algorithms for Minimizing Quartically-Regularized Third-Order Taylor Polynomials
by: Zhu, Wenqi, et al.
Published: (2025)
by: Zhu, Wenqi, et al.
Published: (2025)
A Parameter-Free First-Order Algorithm for Non-Convex Optimization with $\tilde{\mkern1mu O}(ε^{-5/3})$ Global Rate
by: Xiong, Sichao, et al.
Published: (2026)
by: Xiong, Sichao, et al.
Published: (2026)
Random Subspace Cubic-Regularization Methods, with Applications to Low-Rank Functions
by: Cartis, Coralia, et al.
Published: (2025)
by: Cartis, Coralia, et al.
Published: (2025)
Second-order methods for quartically-regularised cubic polynomials, with applications to high-order tensor methods
by: Cartis, Coralia, et al.
Published: (2023)
by: Cartis, Coralia, et al.
Published: (2023)
Tensor-based Dinkelbach method for computing generalized tensor eigenvalues and its applications
by: Chen, Haibin, et al.
Published: (2025)
by: Chen, Haibin, et al.
Published: (2025)
Dimensionality Reduction Techniques for Global Bayesian Optimisation
by: Long, Luo, et al.
Published: (2024)
by: Long, Luo, et al.
Published: (2024)
Nonlinear Dimensionality Reduction Techniques for Bayesian Optimization
by: Long, Luo, et al.
Published: (2025)
by: Long, Luo, et al.
Published: (2025)
A Globally Convergent Third-Order Newton Method via Unified Semidefinite Programming Subproblems
by: Cai, Yubo, et al.
Published: (2026)
by: Cai, Yubo, et al.
Published: (2026)
Randomized Subspace Derivative-Free Optimization with Quadratic Models and Second-Order Convergence
by: Cartis, Coralia, et al.
Published: (2024)
by: Cartis, Coralia, et al.
Published: (2024)
A Derivative-Free Saddle-search Algorithm With Linear Convergence Rate
by: Du, Qiang, et al.
Published: (2026)
by: Du, Qiang, et al.
Published: (2026)
Fast and Numerically Stable Implementation of Rate Constant Matrix Contraction Method
by: Hemmi, Shinichi, et al.
Published: (2024)
by: Hemmi, Shinichi, et al.
Published: (2024)
Error Estimates of the Gain Approximation by Hermite-Galerkin Method in Feedback Particle Filter
by: Wang, Ruoyu, et al.
Published: (2026)
by: Wang, Ruoyu, et al.
Published: (2026)
The Essential Best and Average Rate of Convergence of the Exact Line Search Gradient Descent Method
by: Yu, Thomas
Published: (2023)
by: Yu, Thomas
Published: (2023)
Approximate Vertex Enumeration
by: Löhne, Andreas
Published: (2020)
by: Löhne, Andreas
Published: (2020)
Nyström Approximation on Manifolds
by: Nie, Hantao, et al.
Published: (2026)
by: Nie, Hantao, et al.
Published: (2026)
Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation Models
by: Cohen, Jeremy E., et al.
Published: (2024)
by: Cohen, Jeremy E., et al.
Published: (2024)
Scalable Approximate Optimal Diagonal Preconditioning
by: Gao, Wenzhi, et al.
Published: (2023)
by: Gao, Wenzhi, et al.
Published: (2023)
Solving Implicit Inverse Problems with Homotopy-Based Regularization Path
by: Parodi, Davide, et al.
Published: (2025)
by: Parodi, Davide, et al.
Published: (2025)
Mixed-Derivative Total Variation
by: Guillemet, Vincent, et al.
Published: (2025)
by: Guillemet, Vincent, et al.
Published: (2025)
A Framework for Approximating Perturbed Optimal Control Problems
by: Link, Riley, et al.
Published: (2024)
by: Link, Riley, et al.
Published: (2024)
Approximation of Algebraic Riccati Equations with Generators of Noncompact Semigroups
by: Cheung, James
Published: (2022)
by: Cheung, James
Published: (2022)
On the Approximation of Operator-Valued Riccati Equations in Hilbert Spaces
by: Cheung, James
Published: (2023)
by: Cheung, James
Published: (2023)
Well-Posedness and Efficient Algorithms for Inverse Optimal Transport with Bregman Regularization
by: Bao, Chenglong, et al.
Published: (2025)
by: Bao, Chenglong, et al.
Published: (2025)
Regularized methods via cubic model subspace minimization for nonconvex optimization
by: Bellavia, Stefania, et al.
Published: (2023)
by: Bellavia, Stefania, et al.
Published: (2023)
Approximate Projections onto the Positive Semidefinite Cone Using Randomization
by: Jones, Morgan, et al.
Published: (2024)
by: Jones, Morgan, et al.
Published: (2024)
Scalable Second-Order Optimization Algorithms for Minimizing Low-rank Functions
by: Tansley, Edward, et al.
Published: (2025)
by: Tansley, Edward, et al.
Published: (2025)
Spiking Neural Networks: a theoretical framework for Universal Approximation and training
by: Biccari, Umberto
Published: (2025)
by: Biccari, Umberto
Published: (2025)
Tight Convergence Rates in Gradient Mapping for the Difference-of-Convex Algorithm
by: Rotaru, Teodor, et al.
Published: (2025)
by: Rotaru, Teodor, et al.
Published: (2025)
Adaptive Approximations of Inclusions in a Semilinear Elliptic Problem Related to Cardiac Electrophysiology
by: Jin, Bangti, et al.
Published: (2025)
by: Jin, Bangti, et al.
Published: (2025)
Optimal Control using Composite Bernstein Approximants
by: MacLin, Gage, et al.
Published: (2024)
by: MacLin, Gage, et al.
Published: (2024)
On the Crouzeix-Raviart Finite Element Approximation of Phase-Field Dependent Topology Optimization in Stokes Flow
by: Jin, Bangti, et al.
Published: (2025)
by: Jin, Bangti, et al.
Published: (2025)
The State-Dependent Riccati Equation in Nonlinear Optimal Control: Analysis, Error Estimation and Numerical Approximation
by: Saluzzi, Luca
Published: (2025)
by: Saluzzi, Luca
Published: (2025)
Numerical Analysis on Neural Network Projected Schemes for Approximating One Dimensional Wasserstein Gradient Flows
by: Zuo, Xinzhe, et al.
Published: (2024)
by: Zuo, Xinzhe, et al.
Published: (2024)
Smoothed Moreau-Yosida Tensor Train Approximation of State-constrained Optimization Problems under Uncertainty
by: Antil, Harbir, et al.
Published: (2023)
by: Antil, Harbir, et al.
Published: (2023)
Derivative-free optimization is competitive for aerodynamic design optimization in moderate dimensions
by: Plaban, Punya, et al.
Published: (2025)
by: Plaban, Punya, et al.
Published: (2025)
Symplectic Methods in Deep Learning
by: Maslovskaya, Sofya, et al.
Published: (2024)
by: Maslovskaya, Sofya, et al.
Published: (2024)
Interpolation-Based Gradient-Error Bounds for Use in Derivative-Free Optimization of Noisy Functions
by: Marchetti, Alejandro G., et al.
Published: (2025)
by: Marchetti, Alejandro G., et al.
Published: (2025)
Error Analysis of Sampling Algorithms for Approximating Stochastic Optimal Control
by: Joshi, Anant A., et al.
Published: (2025)
by: Joshi, Anant A., et al.
Published: (2025)
An Abstract Lyapunov Control Optimizer: Local Stabilization and Global Convergence
by: Bensaid, Bilel, et al.
Published: (2024)
by: Bensaid, Bilel, et al.
Published: (2024)
Similar Items
-
Global Convergence of High-Order Regularization Methods with Sums-of-Squares Taylor Models
by: Zhu, Wenqi, et al.
Published: (2024) -
Global Optimality Characterizations and Algorithms for Minimizing Quartically-Regularized Third-Order Taylor Polynomials
by: Zhu, Wenqi, et al.
Published: (2025) -
A Parameter-Free First-Order Algorithm for Non-Convex Optimization with $\tilde{\mkern1mu O}(ε^{-5/3})$ Global Rate
by: Xiong, Sichao, et al.
Published: (2026) -
Random Subspace Cubic-Regularization Methods, with Applications to Low-Rank Functions
by: Cartis, Coralia, et al.
Published: (2025) -
Second-order methods for quartically-regularised cubic polynomials, with applications to high-order tensor methods
by: Cartis, Coralia, et al.
Published: (2023)