Advances in High-Dimensional Data Analysis and Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Probability and Statistics".
Deadline for manuscript submissions: 28 February 2025 | Viewed by 34
Special Issue Editor
Special Issue Information
Dear Colleagues,
This Special Issue compiles innovative statistical methodologies, applications, and data analyses that address the challenges and opportunities presented by high-dimensional data across various scientific disciplines. High-dimensional data, characterized by a large number of variables relative to the number of observations, are becoming increasingly prevalent in fields such as omics, electronic health records, imaging, and finance. This Special Issue will feature a broad range of articles, including the following. Novel statistical techniques: introduction of new statistical models and inference methods tailored to handle high-dimensional datasets, ensuring robustness and accuracy in the face of data complexity. Machine learning algorithms: development and application of advanced machine learning algorithms that can efficiently manage and analyze high-dimensional data, uncovering hidden patterns and driving predictive analytics. Dimensionality reduction methods: innovative approaches to reduce the dimensionality of data while preserving essential information, facilitating more efficient data analysis and visualization. Computational techniques: exploration of novel computational methods and tools designed to process high-dimensional data more effectively, addressing issues related to computational cost and scalability. Practical applications: case studies and practical applications demonstrating the successful implementation of high-dimensional data analysis techniques in various domains, such as personalized medicine, biomarker identification, financial modeling, and image recognition.
Dr. Ran Dai
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
- high-dimensional data
- statistical techniques
- machine learning algorithms
- dimensionality reduction methods
