Special Issue "Recent Advances in Numerical Algorithms for Machine Learning"

Dear Colleagues,

Numerical algorithms have an important role in a variety of machine learning domains, including natural language processing, computer vision, biometrics, autonomous systems, etc.

This Special Issue aims to highlight recent advancements in numerical algorithms for machine learning, especially those that tackle open research questions related to methodological novelty, performance or theoretical justification. 

We welcome original research articles related to the field which ideally address the widest possible audience. Research areas may include (but are not limited to) the following: 

• New and improved numerical algorithms for machine learning;
• Novel applications of numerical algorithms for machine learning;
• Novel applications of numerical machine learning algorithms in medicine;
• Machine learning and music—mathematics meets the fine arts;
• Feature extraction and representation learning;
• Complexity, optimization and validation;
• Contextual awareness and adaptability;
• Approximation and heuristics;
• Theoretical results. 

We look forward to receiving your contributions.

Prof. Dr. Milan Gnjatović
Prof. Dr. Nemanja Maček
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Axioms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• numerical algorithms
• machine learning
• deep learning
• representation learning
• complexity, optimization and validation
• contextual awareness and adaptability
• natural language processing
• computer vision
• biometrics