When you listen to quantum enthusiasts, you may feel tempted to treat QML as an emerging silver bullet, which it isn’t.

Advances in machine learning for materials science, data-driven materials prediction, autonomous synthesis and characterization, and data-guided high-throughput exploration, can now significantly ...

Two new studies from the Department of Computational Biomedicine at Cedars-Sinai are advancing what we know about using ...

Upon completion of this course, participants should be able to: ¿ Understand how big data and machine learning can complement traditional data and analytical techniques in macroeconomic analysis and ...

In addition, the book includes an introduction to artificial neural networks, convex optimization, multi-objective optimization and applications of optimization in machine learning. About the Purdue ...