References
- Brent R.P., Algorithms for Minimization Without Derivatives, Courier Corporation, Dover Publication, New York, USA, 2013.
- Wu X., Shao H., Liu P., Zhang Y., Zhuo Y., An efficient conjugate gradient-based algorithm for unconstrained optimization and its projection extension to large-scale constrained nonlinear equations with applications in signal recovery and image denoising problems, Journal of Computational and Applied Mathematics, 422, 114879, 2023.
- Davidon W.C., Variable metric method for minimization, Argonne National Laboratory, Lemont, Illinois, (Master Thesis), ANL-5990, University of Chicago, USA, 1959.
- Fletcher R., Powell M.J.D., A rapidly convergent descent method for minimization, The Computer Journal, 6(2), 163–168, 1963.
- Hestenes M.R., Stiefel E., Methods of conjugate gradients for solving linear systems, Journal of Research of the National Bureau of Standards, 49(6), 409–436, 1952.
- Fletcher R., Reeves C.M., Function minimization by conjugate gradients, The Computer Journal, 7(2), 149–154, 1964.
- Nocedal J., Wright S.J., Numerical Optimization (2nd Ed.), Springer, USA, 2006.
- Yousif O.O.O., Mohammed M.A.Y., Saleh M.A., Elbashir M.K., A criterion for the global convergence of conjugate gradient methods under strong Wolfe line search, Journal of King Saud University-Science, 34(8), 102281, 2022.
- Kelley C.T., Iterative Methods for Optimization, SIAM, Philadelphia, USA, 1999.
- Zhang L., An improved Wei-Yao-Liu nonlinear conjugate gradient method for optimization computation, Applied Mathematics and Computation, 215(6), 2269–2274, 2009.
- Doikov N., Nesterov Y., Gradient regularization of Newton method with Bregman distances, Mathematical Programming, 204, 1–25, 2024.
- Stanimirović P.S., Shaini B.I., Sabi’u J., Shah A., Petrović M.J., Ivanov B., Cao X., Stupina A., Li S., Improved gradient descent iterations for solving systems of nonlinear equations, Algorithms, 16(64), 1–23, 2023.
- Gupta S.D., Freund R.M., Sun X.A., Taylor A., Nonlinear conjugate gradient methods: worst-case convergence rates via computer-assisted analyses, arXiv:2301.01530, 2023.
- Ortega J.M., Rheinboldt W.C., Iterative solution of nonlinear equations in several variables, SIAM, Philadelphia, USA, 1999.
- Hestenes M.R., Conjugate Direction Methods in Optimization (Vol:12), Springer, New York, USA, 1980.
- Russak I.B., Convergence of the conjugate Gram-Schmidt method, Journal of Optimization Theory and Applications, 33, 163–173, 1981.
- Stein J.I., Conjugate Direction Algorithms in Numerical Analysis and Optimization, (Final Report), U.S. Army Research Office, DAHC 04-74-G-0006, National Science Foundation GP-40175, The University of Toledo, USA, 1975.
- Stein J.I., Raihen M.N., Convergence rates for Hestenes’ Gram-Schmidt conjugate direction method without derivatives in numerical optimization, AppliedMath, 3(2), 268–285, 2023.
- Dennemeyer R.F., Mookini E.H., CGS algorithms for unconstrained minimization of functions, Journal of Optimization Theory and Applications, 16(1–2), 67–85, 1975.
- Ortega J.M., Rheinboldt W.C., On a class of approximate iterative processes, Archive for Rational Mechanics and Analysis, 23, 352–365, 1967.
- Raihen N., Convergence rates for Hestenes’ Gram-Schmidt conjugate direction method without derivatives in numerical optimization, (Master Thesis), University of Toledo, USA, 2017.
- Andrei N., Nonlinear Conjugate Gradient Methods for Unconstrained Optimization, Springer, Switzerland, 2020.
- Olsen N.C., Private Communication to Ivie Stein Jr., Consultant, Lockheed, Palmdale, California, USA, 2005.
- Desrochers A., Mohseni S., Quadratic optimization via conjugate directions and projection matrices, 1985 American Control Conference, IEEE, 19–21 June 1985, Boston, Massachusetts, USA, 1684–1688, 1985.
- Stein I., Conjugate gradient methods in Banach spaces, Nonlinear Analysis: Theory Methods and Applications, 63(5–7), e2621–e2628, 2005.