Featuring Yusu Wang, University of California San Diego

Abstract: Machine learning, especially the use of neural netowrks have shown great success in a broad range of applications. Recently, neural approaches have also shown promise in tackling (combinatorial) optimization problems in a data-driven manner. On the other hand, for many problems, especially geometric optimization problems, many beautiful geometric ideas and algorithmic insights have been developed in fields such as theoretical computer science and computational geometry. Our goal is to infuse geometric and algorithmic ideas to the design of neural frameworks so that they can be more effective and generalize better. In this talk, I will give two examples in this direction. The first one is what we call a mixed Neural-algorithmic framework for the Steiner Tree problem in the Euclidean space, leveraging the celebrated PTAS algorithm by Arora. Interestingly, here the model complexity can be made independent of the input point set size. The second one is an neural architecture for approximating the Wasserstein distance between point sets, whose design /analysis uses a geometric coreset idea. 

Bio: Yusu Wang is currently Professor in the Halicioglu Data Science Institute at University of California, San Diego, where she also serves as the Director for the NSF National AI Institute TILOS. Prior to joining UCSD, she was Professor in the Computer Science and Engineering Department at the Ohio State University. She obtained her PhD degree from Duke University in 2004, and from 2004-2005, she was a post-doctoral fellow at Stanford University. Yusu Wang primarily works in the fields of geometric and topological data analysis, especially the use of these ideas in modern machine learning. She received DOE Early Career Principal Investigator Award in 2006, and NSF Career Award in 2008. She is on the editorial boards for SIAM Journal on Computing (SICOMP) and Journal of Computational Geometry (JoCG). She is a member of the Computational Geometry Steering Committee, as well as a member of the AATRN Advisory Committee. She also serves in the SIGACT CATCS committee and AWM Meetings Committee.