Cover Image

Quasi-Newton methods for minimizing a quadratic function subject to uncertainty

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Peng, Shen, Canessa, Gianpiero, Ek, David, Forsgren, Anders
Format:	Preprint
Published:	2021
Subjects:	Optimization and Control 90C20, 90C53, 90C15
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Stochastic Quasi-Newton Method in the Absence of Common Random Numbers
by: Menickelly, Matt, et al.
Published: (2023)

A Single-Loop Stochastic Proximal Quasi-Newton Method for Large-Scale Nonsmooth Convex Optimization
by: Song, Yongcun, et al.
Published: (2024)

Lispchitz modulus of the argmin mapping in convex quadratic optimization
by: Cánovas, María Josefa, et al.
Published: (2025)

Bundle methods with quadratic cuts for deterministic and stochastic strongly convex optimization problems
by: Guigues, Vincent, et al.
Published: (2017)

Operation of an ambulance fleet under uncertainty
by: Guigues, Vincent, et al.
Published: (2022)

Proximal Limited-Memory Quasi-Newton Methods for Nonsmooth Nonconvex Optimization
by: Dahl, Simeon vom, et al.
Published: (2026)

On the convexity for the range set of two quadratic functions
by: Nguyen, Huu-Quang, et al.
Published: (2025)

Practical Regularized Quasi-Newton Methods with Inexact Function Values
by: Hamaguchi, Hiroki, et al.
Published: (2026)

An uncertainty model for positive-valued parameters with application to robust optimization
by: Tanaka, Tatsuya, et al.
Published: (2026)

Approximating Hessian matrices using Bayesian inference: a new approach for quasi-Newton methods in stochastic optimization
by: Carlon, Andre, et al.
Published: (2022)

Extended Triangle Inequalities for Nonconvex Box-Constrained Quadratic Programming
by: Anstreicher, Kurt M., et al.
Published: (2025)

QPALM: A Proximal Augmented Lagrangian Method for Nonconvex Quadratic Programs
by: Hermans, Ben, et al.
Published: (2020)

Proximal Quasi-Newton Method for Composite Optimization over the Stiefel Manifold
by: Wang, Qinsi, et al.
Published: (2025)

A new envelope function for nonsmooth DC optimization
by: Themelis, Andreas, et al.
Published: (2020)

Hidden convexity of quadratic systems and its application to quadratic programming
by: Huy, Nguyen Quang, et al.
Published: (2026)

Nonsmooth exact penalty methods for equality-constrained optimization: complexity and implementation
by: Diouane, Youssef, et al.
Published: (2024)

Exact SDP relaxations for a class of quadratic programs with finite and infinite quadratic constraints
by: Arima, Naohiko, et al.
Published: (2024)

Novel Limited Memory Quasi-Newton Methods Based On Optimal Matrix Approximation
by: Berglund, Erik, et al.
Published: (2024)

A stochastic use of the Kurdyka-Lojasiewicz property: Investigation of optimization algorithms behaviours in a non-convex differentiable framework
by: Fest, Jean-Baptiste, et al.
Published: (2023)

A low-rank augmented Lagrangian method for doubly nonnegative relaxations of mixed-binary quadratic programs
by: Hou, Di, et al.
Published: (2025)

Tighter yet more tractable relaxations and nontrivial instance generation for sparse standard quadratic optimization
by: Bomze, Immanuel, et al.
Published: (2024)

A linesearch-type normal map-based semismooth Newton method for nonsmooth nonconvex composite optimization
by: Zeng, Hanfeng, et al.
Published: (2026)

Beyond binarity: Semidefinite programming for ternary quadratic problems
by: de Meijer, Frank, et al.
Published: (2026)

Alternating Iteratively Reweighted $\ell_1$ and Subspace Newton Algorithms for Nonconvex Sparse Optimization
by: Wang, Hao, et al.
Published: (2024)

On the asymptotic behavior of a higher-order extrapolation primal-dual interior-point method for nonlinear programming
by: Heeman, Pim, et al.
Published: (2025)

A Frank-Wolfe-based primal heuristic for quadratic mixed-integer optimization
by: Mexi, Gioni, et al.
Published: (2025)

A polynomially solvable case of unconstrained (-1,1)-quadratic fractional optimization
by: Yang, Meijia, et al.
Published: (2024)

A non-monotone trust-region method with noisy oracles and additional sampling
by: Krejic, Natasa, et al.
Published: (2023)

Quasi-Newton Method for Set Optimization Problems with Set-Valued Mapping Given by Finitely Many Vector-Valued Functions
by: Ghosh, Debdas, et al.
Published: (2024)

Parameter-Free Accelerated Quasi-Newton Method for Nonconvex Optimization
by: Marumo, Naoki
Published: (2025)

Improving Quasi-Newton Methods via Image and Projection Operators
by: Ji, Zhenyuan
Published: (2025)

Riemannian Interior Point Methods for Constrained Optimization on Manifolds
by: Lai, Zhijian, et al.
Published: (2022)

New results on the local-nonglobal minimizers of the generalized trust-region subproblem
by: Ai, Wenbao, et al.
Published: (2024)

A Unified Zeroth-Order Proximal Newton-Type Framework for Composite Optimization
by: Liu, Zekun, et al.
Published: (2026)

Convex quadratic sets and the complexity of mixed integer convex quadratic programming
by: Del Pia, Alberto
Published: (2023)

Riemannian Gradient Method with Momentum
by: Leggio, Filippo, et al.
Published: (2026)

A Newton-Kantorovich Inverse Function Theorem in Quasi-Metric Spaces
by: Pinta, Titus
Published: (2025)

PANOC-lite: A simpler and more efficient algorithm for composite minimization
by: Bodard, Alexander, et al.
Published: (2026)

HPR-QP: A dual Halpern Peaceman-Rachford method for solving large-scale convex composite quadratic programming
by: Chen, Kaihuang, et al.
Published: (2025)

A quadratically convergent proximal algorithm for nonnegative tensor decomposition
by: Vervliet, Nico, et al.
Published: (2020)