Publications

Por Max L.N. Gonçalves

Prepints  

       1. Gonçalves, M. L. N. Subsampled cubic regularization method with distinct sample sizes for function, gradient, and Hessian

       2. Gonçalves, D. S., Gonçalves, M. L. N.; Melo, J.G.  A cubic regularization method for multiobjective optimization. 

       3.  Gonçalves, M. L. N. Grapiglia, G.N.. Sub-sampled Trust-Region Methods with Deterministic Worst-Case Complexity Guarantees.

 

Articles in Academic Journals  (Scholar Google Citations click here)

 

  1. Bello-Cruz, Y., Gonçalves, M.L.N.,   Melo, J. G.,  Mohr, C..   A Relative Inexact Proximal Gradient Method With an Explicit Linesearch. [code],  Journal Optim. Theory Appl.,206(9), 1-32, 2025.(pdf)
  2. Gonçalves, D. S., Gonçalves, M. L. N.; Melo, J.G.  Improved convergence rates for the multiobjective Frank-Wolfe method . Journal Optim. Theory Appl., 205(20):1–25,  2025. (pdf).
  3. Gonçalves, M. L. N. Subsampled cubic regularization method for finite-sum minimization.  Optimization, 2024 (pdf)
  4. Gonçalves, M. L. N.; Menezes, T.C. A framework for convex-constrained monotone nonlinear equations and its special cases. Computational and Applied Mathematics, 2024   (pdf)  [code]
  5. Gonçalves, D. S., Gonçalves, M. L. N.; Melo, J.G.. An away-step Frank-Wolfe algorithm for constrained multiobjective optimization. Computational Optimization and Applications, 88, 759-781, 2024.
  6. Adona, V.A.; Gonçalves, M. L. N. An inexact version of the symmetric proximal ADMM for solving separable convex optimization.  Numerical Algorithms, 94, 1--28, 2023. (pdf)
  7. Bello-Cruz, Y., Gonçalves, M. L. N., Krislock, N.. On FISTA with a relative error condition.  Computational Optimization and Applications, 84, 295-318, 2023. (pdf)  [code]
  8. Gonçalves, M. L. N., Lima, F.S., Prudente, L.F.  A study of Liu-Storey conjugate gradient methods for vector optimization.   Applied Mathematics and Computation, 425, 127099, 2022. (pdf) 
  9. Gonçalves, M. L. N.; Melo, J. G.; Monteiro, R. D. C.. Projection-free accelerated method for convex optimization. Optimization methods and software, 37, 214-240, 2022. (pdf)
  10. Gonçalves, M. L. N., Lima, F.S., Prudente, L.F. Globally convergent Newton-type methods for multiobjective optimization.  Computational Optimization and Applications,83, 403-434, 2022. (pdf.)
  11. Grapiglia, G.N.; Gonçalves, M. L. N.; Silva, G.N. A Cubic Regularization of  Newton's Method with Finite-Difference Hessian Approximations.  Numerical Algorithms, 90, 607–630 (2022). (pdf)
  12. Gonçalves, D. S., Gonçalves, M. L. N.; Menezes, T.C.. Inexact variable metric method for convex-constrained optimization problems.  Optimization, 71(1), 145-163, 2022 (pdf)
  13. Gonçalves, D. S., Gonçalves, M. L. N.; Oliveira, F.R.. An inexact projected LM type algorithm for constrained nonlinear systems.   Journal of Computational and Applied Mathematics, 391, 113-421, 2021  (pdf)
  14. Adona, V.A.; Gonçalves, M. L. N.; Melo, J. G. An  inexact proximal generalized alternating direction method of multipliers. Computational Optimization and Applications, 76(3), 621-647, 2020. (pdf)
  15. Gonçalves, M. L. N.; Prudente, L.F. On the extension of the Hager-Zhang conjugate gradient method for vector optimization.  Computational Optimization and Applications, 76(3), 899-916, 2020. (pdf)
  16. Gonçalves, M. L. N.; Oliveira, F.R. On the global convergent of an inexact quasi-Newton conditional gradient method for constrained nonlinear systems.  Numerical Algorithms, 84(2), 609-631, 2020. (pdf).
  17. Gonçalves, M. L. N.; Menezes, T.C. Gauss-Newton method with approximate projections for solving constrained nonlinear least squares problems.   Journal of Complexity, 58(1), 101459,  2020. (pdf)
  18. Gonçalves, M. L. N.; Melo, J. G.; Monteiro, R. D. C.. On the iteration-complexity of a non-Euclidean hybrid proximal extragradient and a proximal ADMM. Optimization, 69(4), 847-873, 2020. (pdf)
  19. Gonçalves, M. L. N.; Melo, J. G.; Monteiro, R. D. C.. Convergence rate bounds for a proximal ADMM with over-relaxation stepsize parameter for solving nonconvex linearly constrained problems.  Pacific journal of optimization, 15(3), 379-398, 2019. (pdf).
  20. Adona, V.A.; Gonçalves, M. L. N.; Melo, J. G. A Partially Inexact Proximal Alternating Direction Method of Multipliers and Its Iteration-Complexity Analysis.  J. Optim. Theory App., 182(2): 640–666,2019 (pdf).
  21. Adona, V.A.; Gonçalves, M. L. N.; Melo, J. G..  Iteration-complexity of a generalized alternating direction method of multipliers. Journal of Global Optimization, 73(2):331-348, 2019 (pdf).
  22. Gonçalves, M. L. N.; Oliveira, F.R..  An inexact Newton-Like gradient method for constrained nonlinear systems. Applied Numerical Mathematics, Vol 132(1): 22-34, 2018  (pdf)
  23. Gonçalves, M. L. N. On the pointwise iteration-complexity of a dynamic regularized ADMM with over-relaxation stepsize.  Applied Mathematics and Computation, Vol 336 (1),  315-325, 2018 (pdf).
  24. Gonçalves, M. L. N.; Marques Alves, M; Melo, J. G.. Pointwise and ergodic convergence rates of a variable metric proximal ADMM. J. Optim. Theory Appl Vol 177, No.1: pp 448-478, 2018. (pdf)
  25. Gonçalves, M. L. N.; Melo, J. G.; Monteiro, R. D. C.. Improved pointwise iteration-complexity of a regularized ADMM and of a regularized non-Euclidean HPE framework.  SIAM Journal on Optimization, Vol. 27, No. 1 : pp. 379-407, 2017. (pdf)
  26.  Gonçalves, M. L. N.; Melo, J. G. . A Newton conditional gradient method for constrained nonlinear systems. Journal of Computational and Applied Mathematics, 311, p. 473-483, 2016.(pdf)
  27.  Gonçalves, M. L. N. . Inexact Gauss-Newton like methods for injective-overdetermined systems of equations under a majorant condition. Numerical Algorithms, v. 72, p. 377-392, 2016. (pdf)
  28.  Gonçalves, M. L. N.; Melo, J. G. ; Prudente, L. F. . Augmented Lagrangian methods for nonlinear programming with possible infeasibility. Journal of Global Optimization, v. 63, p. 297-318, 2015.(pdf)
  29. Gonçalves, M.L.N.; Oliveira, P.R. . Convergence of the Gauss-Newton method for a special class of systems of equations under a majorant condition. Optimization , v. 64, p. 1-18, 2015. (pdf)
  30.  Ferreira, O. P. ; Gonçalves, M. L. N. ; Oliveira, P. R. . Convergence of the Gauss--Newton Method for Convex Composite Optimization under a Majorant Condition. SIAM Journal on Optimization, v. 23, p. 1757-1783, 2013. (pdf) 
  31. Gonçalves, M.L.N.. Local convergence of the Gauss-Newton method for injective-overdetermined systems of equations under a majorant condition. Computers & Mathematics with Applications, v. 66, p. 490-499, 2013. (pdf)
  32. Ferreira, O.P. ; Oliveira, P.R. ; Gonçalves, M. L. N. . Local convergence analysis of inexact Gauss-Newton like methods under majorant condition. Journal of Computational and Applied Mathematics, v. 236, p. 2487-2498, 2012. (pdf)
  33.  Ferreira, O.P. ; Gonçalves, M.L.N. ; Oliveira, P.R. . Local convergence analysis of the Gauss-Newton method under a majorant condition. Journal of Complexity (Print), v. 27, p. 111-125, 2011. (pdf)
  34.  Ferreira, O. P. ; Gonçalves, M. L. N. . Local convergence analysis of inexact Newton-like methods under majorant condition. Computational Optimization and Applications, v. 48, p. 1-21, 2011. (pdf)

 

Ph. D. Thesis

  1. Gonçalves, M. L. N.. Análise de convergência dos métodos de Gauss-Newton do ponto de vista do princípio majorante, 2011. Thesis-Universidade Federal do Rio de Janeiro. Advisor: Paulo R. Oliveira e Orizon P. Ferreira.


Master Dissertation

  1. Gonçalves, M. L. N.. Convergência local do método de Newton inexato e suas variações do ponto de vista do princípio majorante de Kantorovich, 2007. Dissertation-Universidade Federal de Goiás. Advisor: Orizon P. Ferreira.

 

 

 

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