Mathematical optimization and machine learning are two tools that, at first glance, may seem to have a lot in common.

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 ...

Machine learning uncovers opportunities for business optimization hidden in the data lake by supercharging analysis of ever-more-complex information.

You don’t need to be an expert in machine learning to know that it’s an exceptionally detail-oriented craft. Every step of the machine-learning development process—from preprocessing the data and ...

The Graduate School of Information Science (GSIS) at Tohoku University, together with the Physics and Informatics (PHI) Lab ...

Optimization and statistics are everywhere, touching all engineering disciplines in an ever more sophisticated way. Nowhere are they more important than in the rapidly evolving field of machine ...

But it is important to note that Bayesian optimization does not itself involve machine learning based on neural networks, but what IBM is in fact doing is using Bayesian optimization and machine ...

As more designers employ machine learning (ML) in their systems, they’re moving from simply getting the application to work to optimizing the power and performance of their implementations. Some ...