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Advances in High-Dimensional Data Analysis
This special issue belongs to the section “D1: Probability and Statistics“.
Special Issue Information
Dear Colleagues,
High-dimensional data analysis has been an important focus within theoretical and applied statistics research for more than three decades, with applications areas including biostatistics, bioinformatics, chemistry, ecology, economy, and social sciences. The aim of this Special Issue is to collect research papers that use statistical (methodological, theoretical, or computational) principles for high-dimensional data analysis, as well as scalable optimization methods and applications in important real-world fields.
In this Special Issue, we encourage original research submissions that provide new results in the setting of high-dimensional statistical inference and their applications. Review papers within all aspects of high-dimensional data analysis are also welcome.
Dr. Hong Wang
Dr. Liang Shen
Dr. Xuewei Cheng
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 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
- high-dimensional inference
- feature screening
- variable selection
- dimension reduction
- high-dimensional statistical learning
- machine learning for high-dimensional data
- various applications of high-dimensional analysis approaches
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