Tensor decomposition encompasses a suite of mathematical techniques for expressing high-dimensional data arrays as structured combinations of lower-dimensional factors. By generalising matrix ...

Tensor Complementarity Problems (TCPs) extend the classic linear complementarity framework, seeking vectors that satisfy nonlinear complementarity conditions imposed by higher-order arrays. Eigenvalue ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

Leveraging AI to help analyze and visualize data gathered from a variety of data sets enables data-driven insights and fast analysis without the high costs of talent and technology. In today's ...