Abstract: In this work, we focus on solving non-smooth non-convex maximization problems in multi-group multicast transmission. By leveraging Karush-Kuhn-Tucker (KKT) optimality conditions, we ...
Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...
Over the past few decades, engineers have developed various devices that can create holograms, three-dimensional (3D) or ...
Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
The project implements a strengthened MaxSAT-based Dynamic Discretization Discovery (MaxSAT-DDD) framework for fixed-route train rescheduling. It evaluates and compares several solver configurations ...
This content is provided by FEBA. Many federal employees are hearing headlines about Roth changes and wondering whether long-standing retirement strategies are disappearing. The short answer is ...
Abstract: Bilevel optimization, where one optimization problem is inherently nested within another, has gained significant attention due to its extensive applications in machine learning, such as ...
Consumers trying to score the best deals online may be facing a moving target as retailers increasingly use dynamic pricing. It's a strategy that adjusts prices based on factors including demand, ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results