Mathematical Analysis and Optimization for Machine Learning
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".
Deadline for manuscript submissions: 31 May 2027 | Viewed by 45
Editor
Interests: data science and foundation algorithms of artificial intelligence; high-performance numerical algebra and high-dimensional function approximation theory
Special Issue Information
Dear Colleagues,
The convergence of rigorous mathematical analysis with modern machine learning and optimization has become a defining frontier in scientific computing, driving breakthroughs from industrial digital twins to trustworthy AI systems. This Special Issue seeks to capture the theoretical depth and practical impact of this rapidly evolving intersection.
We invite contributions on mathematical analysis for scientific computing (DAEs, PDEs, spectral methods); the optimization theory (convex/non-convex, sparse relaxation, manifold optimization); graph matching and network analysis (approximate bipartite matching, persistent data structures, structural analysis of constraint systems); optimal transport (Sinkhorn algorithms, Wasserstein metrics, entropic regularization, generative modeling); the machine learning theory (graph neural networks, normalizing flows, neural operators, transformers); AI for science (physics-informed ML, digital twins, real-time simulation, geometric constraint solving); high-performance computing (GPU acceleration, sparse matrix computation) and mathematical foundations of reliable AI systems.
We especially welcome work bridging classical mathematical structures with emerging AI methodologies—graph-theoretic optimization, spectral analysis for dynamic systems and operator-theoretic machine learning.
Dr. Shengxin Zhu
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-anonymized 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
- optimization & algorithms
- graph-theoretic methods
- optimal transport
- machine learning
- AI for science & engineering
- AI systems & reliability
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