Aim & Scope
Mathematical Foundations of Computing (MFC), provides an interdisciplinary forum to promote interaction among mathematicians, computer scientists and statisticians as well as engineers to exchange new ideas and techniques for attacking the pressing challenges in data analysis. The journal aims to provide a place for more understanding and transparency of data analytics in different areas of AI. We welcome high-quality papers in all areas of AI related to the computational and algorithmic aspects of data analysis, with emphasis on innovative theoretical development, methods, and algorithms including, but not restricted to, machine learning, deep learning, and learning theory. [1]
2024
Hermitian-Toeplitz determinant for certain Univalent functions
Mathematical Foundations of Computing , 2024
0
9
Some extensions of Bernstein-type inequalities for integral mean estimation of a polynomial
R Laishangbam , N Singha , B Chanam
Mathematical Foundations of Computing , 2024
0
7
A trainable variational Chan-Vese network based on algorithm unfolding for image segmentation
Z Cui , T Pan , G Yang , ... , W Wei
Mathematical Foundations of Computing , 2024
0
25
Dissipative control for singular Takagi-Sugeno fuzzy systems with random actuator failures
X Zhang , L He , H Ni , ... , J Zhou
Mathematical Foundations of Computing , 2024
0
34
Transformer condition prediction based on data and physical models
Z Guo , H Ma , X Liu , ... , L Wu
Mathematical Foundations of Computing , 2024
0
4
Locally dually flatness properties in cubic $ (alpha, beta) $-Metric
B Tripathi , V Chaubey , D Patel
Mathematical Foundations of Computing , 2024
0
8
Total stability of outcome weighted learning
Mathematical Foundations of Computing , 2024
0
15