Manuscript Topics

This special issue aims to publish research articles which make a substantial impact in the design and the mathematical analysis of machine learning methods and related approximation schemes when applied to computational problems from data science, numerical analysis, operations research, or scientific computing. In particular, this special issue aims to cover research contributions on the construction and the analysis of gradient descent optimization strategies, on the design and the analysis of artificial neural networks and their architectures, on statistical learning problems of different kinds, on applications of machine learning techniques in problems from engineering and finance, on optimal control problems, and on related high-dimensional approximation problems. Submissions to this special issue can also contain numerical simulations in which case the source code should be part of the submission or made publicity available at a repository. There are no page limits and long high-quality articles are also welcome.

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