Evaluation complexity of adaptive cubic regularization methods for convex unconstrained optimization - researchr publication related

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Coralia Cartis, Nicholas I. M. Gould, Philippe L. Toint. Evaluation complexity of adaptive cubic regularization methods for convex unconstrained optimization. Optimization Methods and Software, 27(2):197-219, 2012. [doi]

The following publications are possibly variants of this publication:

Adaptive cubic regularisation methods for unconstrained optimization. Part II: worst-case function- and derivative-evaluation complexityCoralia Cartis, Nicholas I. M. Gould, Philippe L. Toint. mp, 130(2):295-319, 2011. [doi]

Adaptive cubic regularisation methods for unconstrained optimization. Part I: motivation, convergence and numerical resultsCoralia Cartis, Nicholas I. M. Gould, Philippe L. Toint. mp, 127(2):245-295, 2011. [doi]

On the Complexity of Steepest Descent, Newton s and Regularized Newton s Methods for Nonconvex Unconstrained Optimization ProblemsCoralia Cartis, Nicholas I. M. Gould, Philippe L. Toint. siamjo, 20(6):2833-2852, 2010. [doi]

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