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).

Chemical Physics Theory Group, Department of Chemistry, University of Toronto, Toronto, Ontario, Canada M5S 3H6 Department of Physical and Environmental Sciences, University of Toronto Scarborough, ...

Understanding the mechanism of how neural networks learn features from data is a fundamental problem in machine learning. Our work explicitly connects the mechanism of neural feature learning to a ...

Linear Programming has been used to solve optimization problems in banking, forestry, petroleum, and medical industries. Optimization can be completed with linear and non linear models. There are ...

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 ...

Mixed-Integer Linear Programming (MILP) plays an important role across a range of scientific disciplines and within areas of strategic importance to society. The MILP problems, however, suffer from ...

This paper presents a method of equilibrium path analysis and stability analysis of an equilibrium state for a rigid origami, which consists of rigid flat faces connected by straight crease lines ...