A semi-smooth Newton method for general projection equations applied to the nearest correlation matrix problem (2025)
- Authors:
- USP affiliated authors: HAESER, GABRIEL - IME ; ARMIJO, NICOLAS ESTEBAN FUENTEALBA - IME
- Unidade: IME
- DOI: 10.1080/02331934.2025.2547716
- Assunto: PROGRAMAÇÃO MATEMÁTICA
- Keywords: Conic programming; nearest correlation matrix; quadratic programming; semi-smooth Newton method
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Optimization
- ISSN: 0233-1934
- Volume/Número/Paginação/Ano: Publicado online em 2025
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
-
ABNT
ARMIJO, Nicolas Esteban Fuentealba e BELLO-CRUZ, Yunier e HAESER, Gabriel. A semi-smooth Newton method for general projection equations applied to the nearest correlation matrix problem. Optimization, 2025Tradução . . Disponível em: https://doi.org/10.1080/02331934.2025.2547716. Acesso em: 27 dez. 2025. -
APA
Armijo, N. E. F., Bello-Cruz, Y., & Haeser, G. (2025). A semi-smooth Newton method for general projection equations applied to the nearest correlation matrix problem. Optimization. doi:10.1080/02331934.2025.2547716 -
NLM
Armijo NEF, Bello-Cruz Y, Haeser G. A semi-smooth Newton method for general projection equations applied to the nearest correlation matrix problem [Internet]. Optimization. 2025 ;[citado 2025 dez. 27 ] Available from: https://doi.org/10.1080/02331934.2025.2547716 -
Vancouver
Armijo NEF, Bello-Cruz Y, Haeser G. A semi-smooth Newton method for general projection equations applied to the nearest correlation matrix problem [Internet]. Optimization. 2025 ;[citado 2025 dez. 27 ] Available from: https://doi.org/10.1080/02331934.2025.2547716 - On the convergence of iterative schemes for solving a piecewise linear system of equations
- A semi-smooth Newton method for conic projection equations
- On the behavior of Lagrange multipliers in convex and nonconvex infeasible interior point methods
- Constraint qualifications and strong global Convergence properties of an augmented lagrangian method on riemannian manifolds
- A note on linearly dependent symmetric matrices
- Optimality conditions and global convergence for nonlinear semidefinite programming
- A relaxed quasinormality condition and the boundedness of dual augmented lagrangian sequences
- A second-order optimality condition with first- and second-order complementarity associated with global convergence of algorithms
- Optimality condition and complexity analysis for linearly-constrained optimization without differentiability on the boundary
- Condições de otimalidade e algoritmos em otimização não linear
Informações sobre o DOI: 10.1080/02331934.2025.2547716 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
3266627_va_-_A_semi-smoot... |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
