Learning and Optimization in High Dimensions

Many foundational challenges in AI, machine learning, inference, and optimization stem from navigating complex, high-dimensional landscapes. Over recent decades, the statistical physics of disordered systems has contributed numerous analytical and numerical frameworks to address these high-dimensional problems, where data enters as a quenched disorder. The relevance of these research directions is underscored by two recent Nobel prizes awarded to Giorgio Parisi and John Hopfield.

The workshop, taking place at Bocconi University on July 9th-11th, will gather a diverse group of leading physicists, mathematicians, computer scientists, and computational neuroscientists to discuss recent advancements and exchange insights on pressing shared open problems. 

The event will be by invitation only and attendance will be free for students and researchers. The Department of Computing Sciences at Bocconi University will provide financial support for the event.