Abstract: Bilevel optimization involves two levels of optimization, where one optimization problem is nested within the other. The structure of the problem often requires solving a large number of ...

Abstract: This letter proposes a new method to solve convex programming problems with constraints expressed by differential linear matrix inequalities (DLMIs). Initially, feasible solutions of ...

👉 How to write the rule of a function given the table of values. To write the rule of a function from the table is somehow tricky but can be made easier by having prior knowledge of the type of ...

QuatIca was inspired by the pioneering work in quaternion linear algebra, particularly the QTFM (Quaternion Toolbox for MATLAB) developed by Stephen J. Sangwine and Nicolas Le Bihan. Their ...

The use of Linear Complementarity Problems (LCP) is a powerful method for modeling switched systems, particularly in the context of power electronic circuits. Switched circuits are ubiquitous in ...

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 ...

In this paper, a new extrapolation economy cascadic multigrid method is proposed to solve the image restoration model. The new method combines the new extrapolation formula and quadratic interpolation ...

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...

In intervention research, single-case experimental designs are an important way to gain insights into the causes of individual changes that yield high internal validity. They are commonly applied to ...

This paper concerns the more foundational tasks of distributed dense linear algebra. While a single TPU core can already store and operate on large matrices (e.g., of size 16,384, 32,768 in single ...