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 ...

OLA2024 welcomes presentations that cover any aspects of optimization and learning research such as new high-impact applications, parameter tuning, 4th industrial revolution, new research challenges, ...

“Machine learning is normally very data intensive, and it’s difficult to generate a lot of data when you’re using high-quality data from finite element analysis. But the multi-objective Bayesian ...

This paper provides a review and commentary on the past, present, and future of numerical optimization algorithms in the context of machine learning applications. Through case studies on text ...