Personalized algorithms may quietly sabotage how people learn, nudging them into narrow tunnels of information even when they start with zero prior knowledge. In the study, participants using ...

This article was co-authored with Emma Myer, a student at Washington and Lee University who studies Cognitive/Behavioral Science and Strategic Communication. In today’s digital age, social media has ...

Abstract: This article proposes a novel constrained multiobjective evolutionary Bayesian optimization algorithm based on decomposition (named CMOEBO/D) for expensive constrained multiobjective ...

Abstract: Microwave device design increasingly relies on surrogate modeling to accelerate optimization and reduce costly electromagnetic (EM) simulations. This article presents a spectral Bayesian ...

Foundational optimization algorithms are the core driving force behind deep learning, evolving from early stochastic gradient descent (SGD) to the widely adopted Adam family. However, as the scale of ...