On complexity and convergence of high-order coordinate descent algorithms for smooth nonconvex box-constrained minimization (2022)
- Authors:
- USP affiliated authors: BIRGIN, ERNESTO JULIAN GOLDBERG - IME ; MARCONDES, DIAULAS MURIZE SANTANA VIEIRA - IME
- Unidade: IME
- DOI: 10.1007/s10898-022-01168-6
- Subjects: PROGRAMAÇÃO NÃO LINEAR; CÁLCULO DE VARIAÇÕES; CONTROLE ÓTIMO; MÉTODOS NUMÉRICOS; ANÁLISE NUMÉRICA; PESQUISA OPERACIONAL; CIÊNCIA DA COMPUTAÇÃO
- Keywords: Coordinate descent methods; Bound-constrained minimization; Worst-case evaluation complexity
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Journal of Global Optimization
- ISSN: 0925-5001
- Volume/Número/Paginação/Ano: v. 84, p. 527-561, 2022
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
-
ABNT
AMARAL, V. S. et al. On complexity and convergence of high-order coordinate descent algorithms for smooth nonconvex box-constrained minimization. Journal of Global Optimization, v. 84, p. 527-561, 2022Tradução . . Disponível em: https://doi.org/10.1007/s10898-022-01168-6. Acesso em: 30 abr. 2024. -
APA
Amaral, V. S., Andreani, R., Birgin, E. J. G., Marcondes, D. M. S. V., & Martínez, J. M. (2022). On complexity and convergence of high-order coordinate descent algorithms for smooth nonconvex box-constrained minimization. Journal of Global Optimization, 84, 527-561. doi:10.1007/s10898-022-01168-6 -
NLM
Amaral VS, Andreani R, Birgin EJG, Marcondes DMSV, Martínez JM. On complexity and convergence of high-order coordinate descent algorithms for smooth nonconvex box-constrained minimization [Internet]. Journal of Global Optimization. 2022 ; 84 527-561.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/s10898-022-01168-6 -
Vancouver
Amaral VS, Andreani R, Birgin EJG, Marcondes DMSV, Martínez JM. On complexity and convergence of high-order coordinate descent algorithms for smooth nonconvex box-constrained minimization [Internet]. Journal of Global Optimization. 2022 ; 84 527-561.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/s10898-022-01168-6 - Completamento de matrizes de distâncias Euclidianas
- Special issue on nonlinear programming dedicated to the ALIO-INFORMS Joint International Meeting 2010. [Prefácio]
- Low order-value approach for solving VaR-constrained optimization problems
- Large-scale active-set box-constrained optimization method with spectral projected gradients
- A box-constrained optimization algorithm with negative curvature directions and spectral projected gradients
- Spectral projected gradient methods: review and perspectives
- Augmented Lagrangians with possible infeasibility and finite termination for global nonlinear programming
- Foreword special issue dedicated to selected surveys in nonlinear programming. [Apresentação]
- Assessing the reliability of general-purpose Inexact Restoration methods
- Packing circles within ellipses
Informações sobre o DOI: 10.1007/s10898-022-01168-6 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 | 3119115 - On complexity a... | Direct link |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
