Adaptive Regularization Algorithms with Inexact Evaluations for Nonconvex Optimization
Adaptive Regularization Algorithms with Inexact Evaluations for Nonconvex Optimization
A regularization algorithm using inexact function values and inexact derivatives is proposed and its evaluation complexity analyzed. This algorithm is applicable to unconstrained problems and to problems with inexpensive constraints (that is, constraints whose evaluation and enforcement has negligible cost) under the assumption that the derivative of highest degree is …