Special Issue: Contemporary Mathematical Methods for Machine Learning and Deep Learning
Recent advances in artificial intelligence, particularly in machine learning (ML) and deep learning (DL), have brought forth significant challenges and opportunities for mathematical sciences. The development of robust, efficient, and interpretable ML/DL models relies heavily on contemporary mathematical methods, ranging from linear algebra and optimization theory to topology, geometry, and stochastic processes. This special issue aims to bridge the gap between modern mathematics and intelligent systems by focusing on theoretical, numerical, and experimental studies that utilize or contribute to the mathematical foundations of ML/DL.
We welcome original research articles, comprehensive reviews, and insightful perspectives that explore mathematical innovations and their applications in areas such as neural network architectures, learning theory, optimization algorithms, high-dimensional data analysis, and AI interpretability. Special attention will be given to works that highlight the theoretical underpinnings of model performance, convergence, stability, and generalization.
This special issue offers a unique platform for mathematicians, data scientists, and AI researchers to share recent developments that not only enhance the theoretical understanding of machine learning but also provide innovative tools and frameworks for practical implementation. By fostering cross-disciplinary collaboration, we aim to inspire new mathematical questions arising from AI applications and to encourage the formulation of principled approaches to address them.
Keywords:
-Machine Learning
-Deep Learning
-Mathematical Modeling
-Optimization
-Neural Networks
-Theoretical AI
-Numerical Methods
-Functional Analysis
-Geometry in AI
-Computational Mathematics
Guest Editors:
- Assoc. Prof. Dr. Burak Taşcı, Google Scholar: https://scholar.google.com/citations?user=EtQiVkYAAAAJ&hl=tr
- Assoc. Prof. Dr. Fatih Uysal
- Assoc. Prof. Dr. Najib Ben Aoun, Google Scholar:https://scholar.google.com/citations?user=XzD4xzoAAAAJ&hl=tr&oi=ao
Submission Information
Submit it online: http://ojs.wiserpub.com/index.php/CM/user/register
Or send it to the email address: cmeditor@universalwiser.com.
Submission Guideline
https://ojs.wiserpub.com/index.php/CM/about/submissions
For any inquiries about this Special Issue, please contact the Editors via cmeditor@universalwiser.com.