[CFP] JOURNAL OF COMPUTATIONAL MATHEMATICS AND DATA- Learning from Data: From Optimization to Inverse Problems

[Flavia Esposito]

Dear colleagues, 

we are pleased to inform you that the following special issue is now open to receive submissions for possible publications.

The paper will be published in Journal of Computational Mathematics and Data Science (a peer-reviewed open access journal ISSN 2772-4158 https://www.sciencedirect.com/journal/journal-of-computational-mathematics-and-data-science)

Below you can find further information.

Title: Learning from Data: From Optimization to Inverse Problems

Submission Deadline: February 27, 2024

Journal: Journal of Computational Mathematics and Data Science

Submission Guidelines: https://www.journals.elsevier.com/journal-of-computational-mathematics-and-data-science

Webpage: https://www.sciencedirect.com/journal/journal-of-computational-mathematics-and-data-science/about/call-for-papers#learning-from-data-from-optimization-to-inverse-problems

Keywords Topics of interest include but are not limited to:  

-Optimization;Inverse problems;

-Hyperparameter estimation;

-Low-rank decomposition;

-Image reconstruction;

-Image processing;

-Regularization methods;

-Feature extraction

Description:

Over the past decade, machine learning has emerged as a major driving force in the growth of innovation. With the increasing amount of data generated, the research community in this field has expanded rapidly. This development has enabled the creation of interpretative models for learning from data that are precise, reliable, and effective.The rapid development of learning approaches naturally flows in the requirement for mathematical formalization and computational analysis of the related issues. These cover several fields of mathematics, from optimization to inverse problems, encountering several open questions in many real applications.

As the Guest Editors, we warmly invite you to contribute in our Special Issue.

Don't hesitate to forward this message to anyone who could be interested. 

Should you have any questions or require further information, please do not hesitate to reach out.

Thank you very much for your kind consideration and apologies for multiple copies.

Best regards,

--

Flavia Esposito, Ph. D. 

Department of Mathematics

Mi𝛿As research group

University of Bari Aldo Moro

via E. Orabona 4 - 70125 Bari, Italy

Tel: +393287470866

Email: flavia....@uniba.it