Name, image and likeness (NIL) deals have flooded college sports with hundreds of millions of dollars — but universities and team general managers have been operating with little formal oversight, ...

Long sales cycles, low conversion volume, and multi-stage purchase journeys make measurement and attribution harder, creating real obstacles to campaign optimization. For B2Bs and brands selling ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

Matthew is a journalist in the news department at GameRant. He holds a Bachelor's degree in journalism from Kent State University and has been an avid gamer since 1985. Matthew formerly served as a ...

Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech researchers have been developing a neural network made out of strands of DNA instead ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

Search optimization now requires combining traditional SEO with AI-focused GEO and answer-driven AEO strategies AI search usage continues to grow, with 10% of US consumers currently using generative ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. There is a need for design strategies that can support rapid and widespread deployment ...

Abstract: This article is devoted to the distributed convex optimization problem for a class of nonlinear multiagent systems under set constraints. The optimization objective function is composed of ...

Abstract: Decentralized optimization strategies are helpful for various applications, from networked estimation to distributed machine learning. This paper studies finite-sum minimization problems ...