A simple and implementable two-loop smoothing method for semi-infinite minimax problem is given with the discretization parameter and the smoothing parameter being updated adaptively. We prove the global convergence of the algorithm when the steepest descent method or a BFGS type quasi-Newton...

Many discussions have enlarged the literature in Bibliometrics since the Hirsch proposal, the so called h-index. Ranking papers according to their citations, this index quantifies a researcher only by its greatest possible number of papers that are cited at least h times. A closed formula for...

A number of flexible distributions (generalized beta of the second kind, inverse hyperbolic sine (IHS), <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$g$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi>g</mi> </math> </EquationSource> </InlineEquation>-and-<InlineEquation ID="IEq2"> <EquationSource Format="TEX">$$h$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi>h</mi> </math> </EquationSource> </InlineEquation>, Weibull, Burr-3, Burr-12, generalized gamma, reciprocal gamma) are examined in the setting of option-pricing to explore potential improvements over the...</equationsource></equationsource></inlineequation></equationsource></equationsource></inlineequation>

Calibration is a highly challenging task, in particular in multiple yield curve markets. This paper is a first attempt to study the chances and challenges of the application of machine learning techniques for this. We employ Gaussian process regression, a machine learning methodology having many...

Calibration is a highly challenging task, in particular in multiple yield curve markets. This paper is a first attempt to study the chances and challenges of the application of machine learning techniques for this. We employ Gaussian process regression, a machine learning methodology having many...