Abstract: In this brief, we propose a novel real-time numerical algorithm for solving nonlinear model predictive control (NMPC) with convex-concave constraints, which arise in various practical ...

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 ...

Primal-dual methods in online optimization give several of the state-of-the art results in both of the most common models: adversarial and stochastic/random order. Here we try to provide a more ...

Like the rest of its Big Tech cadre, Google has spent lavishly on developing generative AI models. Google’s AI can clean up your text messages and summarize the web, but the company is constantly ...

Computer science involves much more than writing code. It blends technical knowledge —like programming, algorithms and data systems — with soft skills, such as communication and problem-solving.

Abstract: Gauss’s principle of least constraint transforms a dynamics problem into a pure minimization framework. We show that this minimization problem is a Strongly Convex Quadratic Programming ...

ABSTRACT: In this paper, we consider a more general bi-level optimization problem, where the inner objective function is consisted of three convex functions, involving a smooth and two non-smooth ...