Exploring Statistical Learning: Inference, Optimization, and Real-World Applications, 2nd Edition
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: 31 October 2026 | Viewed by 28
Special Issue Editor
Interests: machine learning; data mining; linear and non-linear regression; supervised and unsupervised learning; time series analysis; statistics for finance
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
"Exploring Statistical Learning: Inference, Optimization, and Real-World Applications, 2nd Edition" presents a comprehensive investigation into the multifaceted domain of statistical learning. This Special Issue encompasses a wide spectrum of topics, from foundational principles of inference and optimization to their practical manifestations in real-world contexts. The Issue elucidates the intricacies of statistical learning algorithms and their applications across diverse domains such as finance, healthcare, and marketing through a combination of theoretical insights and empirical studies. This collection bridges the gap between theory and practice, equipping readers with a deeper understanding of statistical learning methodologies and their transformative potential in addressing contemporary data analysis and decision-making challenges.
Dr. Carmela Iorio
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 250 words) can be sent to the Editorial Office for assessment.
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
- statistical learning
- inference
- optimization
- real-world applications
- data analysis
- predictive modeling
- machine learning
- supervised learning
- unsupervised learning
- deep learning
- computational statistics
- model evaluation
- decision-making
- data-driven solutions
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
