EDITORIAL article
Front. Appl. Math. Stat.
Sec. Optimization
This article is part of the Research TopicOptimization for Low-rank Data Analysis: Theory, Algorithms and ApplicationsView all 7 articles
Editorial: Optimization for Low-rank Data Analysis: Theory, Algorithms and Applications
Provisionally accepted
- 1School of Data, Mathematical, and Statistical Sciences, University of Central Florida, Orlando, United States
- 2Department of Mathematics, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, SAR China
- 3Department of Information and Communication Technology, Hilla Limann Technical University, Wa, Upper West Region, Ghana
- 4Department of Mathematics, Tufts University, Medford, United States
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applications. Together, these works illustrate how low-rank optimization continues to shape the landscape 12 of applied mathematics, statistics, and data science.
Keywords: data analytics, dimensionality reduction, Matrix completion, Matrix Factorization, Optimzation, Tensor factorization
Received: 09 Dec 2025; Accepted: 16 Dec 2025.
Copyright: © 2025 Cai, Xia, Ganaa and Tasissa. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Abiy Tasissa
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