Conventional robots, like those used in industry and hazardous environments, are easy to model and control, but are too rigid ...

On the other hand, organizations that train managers to lead AI as part of their teams gain a critical edge. They make better ...

Distributed Machine Learning (DML) systems are utilized to enhance the speed of model training in data centers (DCs) and edge nodes. The Parameter Server (PS) communication architecture is commonly ...

According to “Ace,” the company doesn’t employ any former graders, but its members do have card backgrounds. When asked what ...

The training of molecular models of quantum mechanical properties based on statistical machine learning requires large data sets which exemplify the map from chemical structure to molecular property.

This leading textbook provides a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as ...

More information: Brandon Kriesten et al, Learning PDFs through interpretable latent representations in Mellin space, Physical Review D (2025). DOI: 10.1103/PhysRevD.111.014028 ...

In this letter, we consider the concept of mobile crowd-machine learning (MCML) for a federated learning model. The MCML enables mobile devices in a mobile network to collaboratively train neural ...