Cover Image

Local convergence analysis of stabilized sequential quadratic programming methods for optimization problems in Banach spaces

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Yamakawa, Yuya
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

Superlinear and quadratic convergence of a stabilized sequential quadratic semidefinite programming method for nonlinear semidefinite programming problems
by: Yamakawa, Yuya
Published: (2022)

A strong second-order sequential optimality condition for nonlinear programming problems
by: Li, Huimin, et al.
Published: (2025)

Convergence analysis of a regularized Newton method with generalized regularization terms for convex optimization problems
by: Yamakawa, Yuya, et al.
Published: (2024)

A twice continuously differentiable penalty function for nonlinear semidefinite programming problems and its application
by: Yamakawa, Yuya
Published: (2025)

Second-order sequential optimality conditions for nonlinear semidefinite optimization problems
by: Li, Huimin, et al.
Published: (2025)

Augmented Lagrangian methods for convex optimization with priority constraints via an infeasibility control framework
by: Yamakawa, Yuya, et al.
Published: (2026)

A black-box optimization method with polynomial-based kernels and quadratic-optimization annealing
by: Minamoto, Yuki, et al.
Published: (2025)

Modified Armijo line search in optimization on Riemannian submanifolds with reduced computational cost
by: Sato, Hiroyuki, et al.
Published: (2023)

Local near-quadratic convergence of Riemannian interior point methods
by: Obara, Mitsuaki, et al.
Published: (2025)

A quadratically convergent semismooth Newton method for nonlinear semidefinite programming without generalized Jacobian regularity
by: Feng, Fuxiaoyue, et al.
Published: (2024)

On the convergence of conditional gradient method for unbounded multiobjective optimization problems
by: Chen, Wang, et al.
Published: (2024)

On the sequential convergence of Lloyd's algorithms
by: Portales, Léo, et al.
Published: (2024)

Proximal gradient methods in Banach spaces
by: Wachsmuth, Gerd, et al.
Published: (2025)

Sensitivity analysis for mixed binary quadratic programming
by: Cifuentes, Diego, et al.
Published: (2023)

Finding quadratic underestimators for optimal value functions of nonconvex all-quadratic problems via copositive optimization
by: Gabl, Markus, et al.
Published: (2024)

Mirror descent actor-critic methods for entropy regularised MDPs in general spaces: stability and convergence
by: Zorba, Denis, et al.
Published: (2026)

New reformulations for 0-1 quadratic programming problem using quadratic nonconvex reformulation techniques and valid inequalities
by: Lu, Cheng, et al.
Published: (2026)

Solving quadratic binary optimization problems using quantum SDP methods: Non-asymptotic running time analysis
by: Henze, Fabian, et al.
Published: (2025)

A quadratic Grassmann manifold optimization problem arising from quantum embedding methods
by: Ayral, Thomas, et al.
Published: (2026)

Parallel splitting method for large-scale quadratic programs
by: Vandelli, Matteo, et al.
Published: (2025)

Provably data-driven projection method for quadratic programming
by: Nguyen, Anh Tuan, et al.
Published: (2025)

Near optimal controls for partially observed stochastic linear quadratic problems
by: Sun, Jingrui, et al.
Published: (2025)

Inverse optimal control problem in the non autonomous linear-quadratic case
by: Jean, Frédéric, et al.
Published: (2024)

Global convergence of a modified BFGS-type method based on function information for nonconvex multiobjective optimization problems
by: Yang, Yingxue
Published: (2024)

Q-quadratic convergence of the centralized circumcentered-reflection method under a relative interior condition
by: Bello-Cruz, Yunier
Published: (2026)

Linearly convergent bilevel optimization with single-step inner methods
by: Suonperä, Ensio, et al.
Published: (2022)

Condensed-space methods for nonlinear programming on GPUs
by: Pacaud, François, et al.
Published: (2024)

Fix and Bound: An efficient approach for solving large-scale quadratic programming problems with box constraints
by: Locatelli, Marco, et al.
Published: (2022)

A new polynomially solvable class of quadratic optimization problems with box constraints
by: Hladík, Milan, et al.
Published: (2019)

Inexact subgradient algorithm with a non-asymptotic convergence guarantee for copositive programming problems
by: Nishijima, Mitsuhiro, et al.
Published: (2025)

Slow convergence of the moment-SOS hierarchy for an elementary polynomial optimization problem
by: Henrion, Didier, et al.
Published: (2024)

Some iterative algorithms on Riemannian manifolds and Banach spaces with good global convergence guarantee
by: Truong, Tuyen Trung
Published: (2025)

Locally Lipschitz stability of solutions to a parametric parabolic optimal control problem with mixed pointwise constraints
by: Khanh, Huynh
Published: (2024)

Error bounds, PL condition, and quadratic growth for weakly convex functions, and linear convergences of proximal point methods
by: Liao, Feng-Yi, et al.
Published: (2023)

Weak convergence of the stochastic proximal point method in metric spaces
by: Pischke, Nicholas
Published: (2026)

Tight semidefinite programming relaxations for sparse box-constrained quadratic programs
by: Khajavirad, Aida
Published: (2026)

On semidefinite descriptions for convex hulls of quadratic programs
by: Wang, Alex L., et al.
Published: (2024)

Inverse reinforcement learning by expert imitation for the stochastic linear-quadratic optimal control problem
by: Sun, Zhongshi, et al.
Published: (2024)

The exponential turnpike property for periodic linear quadratic optimal control problems in infinite dimension
by: Trélat, Emmanuel, et al.
Published: (2024)

A flatness proof of the exponential turnpike phenomenon for linear-quadratic optimal control problems
by: Fliess, Michel, et al.
Published: (2026)