The minimization of matrix bandwidth is a cornerstone challenge in computational linear algebra and graph theory, with direct implications for the efficiency of numerical solvers, finite-element ...

Abstract: Orthogonal frequency-division multiplexing (OFDM)-based joint radar communication (JRC) systems have signal distortion when the transmit signal has a high peak-to-average power ratio (PAPR).

Operations research professionals need the best linear programming software for Windows to solve optimization problems. Below we offer a tool that comes with all the essentials to help you perform a ...

ReHLine-Python is the official Python implementation of ReHLine, a powerful solver for large-scale empirical risk minimization (ERM) problems with convex piecewise linear-quadratic (PLQ) loss ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...

Abstract: We illustrate some recent results on exact solutions to discrete-time l 1-norm minimization problems with convolution constraints. A fixed-point property for this class of problems is ...

Physics-Informed Neural Networks (PINN) are neural networks encoding the problem governing equations, such as Partial Differential Equations (PDE), as a part of the neural network. PINNs have emerged ...

Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia. Operating a software company needs to run without pouring a lot of money. At the same time, company ...

This paper explores the mathematics behind optimal portfolio construction when relative utility and risk are considered together in a general sense. I derive the portfolio optimization problems when ...