American Institute of Mathematical Sciences

Mathematical Foundations of Computing (MFC), indexed in ESCI, provides an interdisciplinary forum to promote interaction among mathematicians, computer scientists and statisticians as well as engineers to exchange new ideas and techniques for attacking the pressing challenges in data analysis. The journal aims to provide a place for more understanding and transparency of data analytics in different areas of AI. We welcome high-quality papers in all areas of AI related to the computational and algorithmic aspects of data analysis, with emphasis on innovative theoretical development, methods, and algorithms including, but not restricted to, machine learning, deep learning, and learning theory.

All papers will undergo a thorough peer reviewing process unless the subject matter of the paper does not fit the journal, in which case the author will be informed promptly. Every effort will be made to secure a decision in three months and accepted papers are published within two months.

• AIMS is a member of COPE. All AIMS journals adhere to the publication ethics and malpractice policies outlined by COPE.
• Publishes 4 issues a year in February, May, August and November.
• Publishes online only.
• Archived in Portico and CLOCKSS.
• MFC is a joint publication of the American Institute of Mathematical Sciences and Qufu Normal University. All rights reserved.