[1] Andrei, N. An unconstrained optimization test functions, Adv. Model. Optim. 10 (2008), 147–161.
[2] Awwal, A.M., Sulaiman, I.M., Malik, M., Mamat, M. and Kumam, P.K. Sitthithakerngkiet, A spectral RMIL conjugate gradient method for un-constrained optimization with applications in portfolio selection and mo-tion control, IEEE Access, 9 (2021), 75398–75414.
[3] Boente, G. and Fraiman, R. Nonparametric regression estimation, J. Multivariate Anal. 29 (1989), 180–198.
[4] Bongartz, I., Conn, A.R., Gould, N. and Toint, P.L. Constrained and unconstrained testing environment, ACM Trans. Math. Softw. 21 (1995), 123–160.
[5] Collomb, G., Hardle, W. and Hassani, S. A note on prediction via es-timation of the conditional mode function, J. Stat. Plan. Inference, 15 (1987), 227–236.
[6] Dai, Y.H. and Yuan, Y. A nonlinear conjugate gradient method with a strong global convergence property, SIAM J, Optim. 10 (1999), 177–182.
[7] Dai, Y.H. and Yuan, Y. Nonlinear conjugate gradient methods, Shanghai Scientific and Technical Publishers, 2000.
[8] Dolan, E.D. and Morè, J. J. Benchmarking optimization software with performance profiles, Math. Program. 91 (2002), 201–213.
[9] Du, X.W., Zhang, P. and Ma, W. Some modified conjugate gradient methods for unconstrained optimization, J. Comput. Appl. Math. 305 (2016), 92–114.
[10] Fletcher, R. Practical methods of optimization, Wiley, New York, 1987.
[11] Fletcher, R. and Reeves, C. Function minimization by conjugate gradi-ents, Comput. J. 7 (1964), 149–154.
[12] Hager, W.W. and Zhang, H. A survey of nonlinear conjugate gradient methods, Pacific J. Optim. 2 (2006), 35–58.
[13] Hestenes, M.R. and Stiefel, E.L. Methods of conjugate gradients for solv-ing linear systems, J. Res. Nation. Bur. Stand. 49 (1952), 409–436.
[14] Huang, H. A new conjugate gradient method for nonlinear unconstrained optimization problems, J. Hunan Univ. 44 (2014), 141–145.
[15] Huang, H., Wei, Z. and Yao, S. The proof of the sufficient descent con-dition of the Wei-Yao-Liu conjugate gradient method under the strong Wolfe-Powell line search, Appl. Math. Comput. 189 (2007), 1241–1245.
[16] Liu, Y. and Storey, C. Efficient generalized conjugate gradient algo-rithms, J. Optim. Theory Appl. 69 (1991), 129–137.
[17] Ma, G., Lin, H., Jin, W. and Han, D. Two modified conjugate gradi-ent methods for unconstrained optimization with applications in image restoration problems, J.Appl. Math. Comput. (2022), 1–26.
[18] Mehamdia, A.E., Chaib, Y. and Bechouat, T. Two modified conju-gate gradient methods for unconstrained optimization and applications, RAIRO - Oper. Res. 57 (2023), 333–350.
[19] Polak, E. and Ribière, G. Note sur la convergence de directions con-juguée, Revue Francaise d’Informatique et de Recherche Opérationnelle, 16 (1969), 35–43.
[20] Polyak, B.T. The conjugate gradient method in extreme problems, Com-put. Math. Math. Phys. 9 (1969), 94–112.
[21] Powell, M.J.D. Restart procedures for the conjugate gradient method, Math. Program.12 (1977), 241–254.
[22] Powell, M.J.D. Nonconvex minimization calculations and the conjugate gradient method, Lect. Notes Math. 1066 (1984), 122–141.
[23] Samanta, M. and Thavaneswaran, A. Nonparametric estimation of the conditional mode, Commun. Stat. - Theory Methods, 16 (1990), 4515–4524.
[24] Wei, Z., Yao, S. and Liu, L. The convergence properties of some new con-jugate gradient methods, Appl. Math.Comput. 183 (2006), 1341–1350.
[25] Yao, S., Wei, Z. and Huang, H. A notes about WYL’s conjugate gradient method and its applications, Appl. Math. Comput. 191 (2007), 381–388.
[26] Zhang, L. An improved Wei-Yao-Liu nonlinear conjugate gradient method for optimization computation, Appl. Math. Comput. 6 (2009), 2269–2274.
[27] Zoutendijk, G. Nonlinear programming computational methods, Integer and Nonlinear Programming, (1970), 37–86.
