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Nonlinear Conjugate Gradient Methods for Unconstrained Optimization

N. Andrei

2020Springer Optimization and Its Applications

DOI: 10.1007/978-3-030-42950-8

tlooto Summary

A review on conjugate gradient methods for unconstrained optimization is given, characterized by low memory requirements and strong local and global convergence properties.

Abstract

Abstract is not available.

Citation format

ANDREI, N. Nonlinear conjugate gradient methods for unconstrained optimization. Springer Optimization and Its Applications, 2020.