A class of nonmonotone conjugate gradient methods for nonconvex functions
The authors consider the global convergence of a class of nonmonotone conjugate gradient methods for unconstrained optimization problems \(\min_{x\in\mathbb{R}^n} f(x)\), where \(f(x)\) is a nonconvex function. The paper extends the results for convex functions to nonconvex functions. No numerical tests are given.
scientific article; zbMATH DE number 1802903