Abstract: To study optimal control and disturbance attenuation problems, two prominent-and somewhat alternative-strategies have emerged in the last century: dynamic programming (DP) and Pontryagin's ...

Learn how to solve problems using linear programming. A linear programming problem involves finding the maximum or minimum value of an equation, called the objective functions, subject to a system of ...

Learn how to solve problems using linear programming. A linear programming problem involves finding the maximum or minimum value of an equation, called the objective functions, subject to a system of ...

Russell (Rust Scientific Library) helps develop high-performance computations involving linear algebra, sparse linear systems, numerical mathematics (continuation), differential equations, statistics, ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using pseudo-inverse training. Compared to other training techniques, such as stochastic gradient descent, ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

Integer linear programming can help find the answer to a variety of real-world problems. Now researchers have found a much faster way to do it. Inspired by the results of a game-playing neural network ...

Abstract: Recent work (Rantzer, 2022) formulated a class of optimal control problems involving positive linear systems, linear stage costs, and elementwise constraints on control. It was shown that ...

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 ...

1 Department of Basic Sciences and Humanities, University of Asia Pacific, Dhaka, Bangladesh. 2 General Education Department, City University, Dhaka, Bangladesh. 3 Department of Mathematics, ...