Statistical Machine Learning: Models and Its Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D: Statistics and Operational Research".
Deadline for manuscript submissions: 31 January 2026 | Viewed by 49
Special Issue Editor
Special Issue Information
Dear Colleagues,
I invite you to submit your latest research to this Special Issue titled "Statistical Machine Learning: Models and Its Applications". This Special Issue highlights the latest advancements, theoretical foundations, and innovative applications of statistical machine learning (SML) in diverse fields. In the era of data explosion, various application domains strive to uncover hidden insights within data and leverage machine learning, artificial intelligence (AI), and statistical methods to address various clinical and practical challenges. As machine learning techniques continue to evolve, statistical methods play a pivotal role in ensuring robust, interpretable, and efficient models. This Special Issue aims to bring together researchers, practitioners, and experts to explore the intersection of statistical methods and machine learning algorithms, fostering the development of new insights and practical solutions.
Topics of Interest
We welcome submissions on topics including, but not limited to, the following:
- The development of novel statistical machine learning models and algorithms.
- Statistical learning in high-dimensional data and big data environments.
- Applications of statistical machine learning in finance, healthcare, bioinformatics, social sciences, and other domains.
- Methods or applications for data mining and text mining.
- Interpretability and fairness in machine learning models through statistical techniques.
Dr. Charlotte Wang
Guest Editor
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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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.
Keywords
- machine learning
- statistical learning
- data mining
- data science
- data visualization
- feature engineering
- generative AI
- statistical modeling
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