Researchers have developed a machine learning workflow to optimize the output force of photo-actuated organic crystals. Using LASSO regression to identify key molecular substructures and Bayesian ...

Trustwise, the AI trust and optimization company, in collaboration with researchers from the New York University (NYU) Center for Data Science and Tandon School of Engineering, have unveiled a ...

From predictive analytics to autonomous control, AI is making renewable energy systems smarter, faster, and more efficient.

In a rapidly evolving digital landscape, machine learning is at the forefront of computational advancements, revolutionizing industries from healthcare to finan ...

Abstract: Bayesian optimization (BO) is a sequential approach for optimizing black-box objective functions using zeroth-order noisy observations. In BO, Gaussian processes (GPs) are employed as ...

In this article, a local multi-constraint modeling-Bayesian optimization (BO) with region partitioning is proposed, aiming to provide a general optimization solution for high-dimensional ...

A research team led by Associate Professor Sun Yifei from the School of Energy Science at Xiamen University, in collaboration with Professor Tu Xin from the ...

A recent study introduces an advanced anomaly-based intrusion detection system (IDS) designed to address the increasing cyber ...