Special Issue: Mathematics of Machine Learning and Related Topics

Guest Editors

Prof. Arnulf Jentzen
Applied Mathematics: Institute for Analysis and Numerics, Faculty of Mathematics and Computer Science, University of Münster, Germany & School of Data Science and Shenzhen Research Institute of Big Data, The Chinese University of Hong Kong, Shenzhen, China
Email: ajentzen@uni-muenster.de, ajentzen@cuhk.edu.cn


Prof. Thomas Kruse
Institute of Mathematics, University of Giessen, Germany
Email: thomas.kruse@math.uni-giessen.de

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.


For Instructions for authors, please visit
https://www.aimspress.com/era/news/solo-detail/instructionsforauthors
Please submit your manuscript to online submission system
https://aimspress.jams.pub/

Paper Submission

All manuscripts will be peer-reviewed before their acceptance for publication. The deadline for manuscript submission is 31 October 2022

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