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Improved worst-case evaluation complexity for potentially rank-deficient nonlinear least-Euclidean-norm problems using higher-order regularized models

Coralia Cartis(cartis***at***maths.ox.ac.uk)
Nicholas I M Gould(nick.gould***at***stfc.ac.uk)
Philippe L Toint(phtoint***at***fundp.ac.be)

Abstract: We present an improved evaluation complexity bound for nonlinear least squares problems using higher order regularization methods.


Category 1: Nonlinear Optimization

Citation: Technical Report NA 15-17, Numerical Analysis Group, University of Oxford, 2015

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Entry Submitted: 11/19/2015
Entry Accepted: 11/19/2015
Entry Last Modified: 11/19/2015

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