Title: Deep AUC Maximization and Applications in Medical Image Classification
Abstract: In this talk, I will present our recent research on a new learning paradigm of deep learning by AUC maximization. I will present a new surrogate loss for AUC and non-convex min-max optimization algorithms for solving deep AUC maximization problem. I will also talk about our results on Stanford CheXpert competition, on which our method is ranked at the 1st place as of today.
Bio: Tianbao Yang is an associate Professor of Computer Science at the University of Iowa. His research interests center round optimization, machine learning and AI. He received the best student paper award at COLT in 2012, NSF Career Award in 2019, and was named Dean’s Excellence in Research Scholar. In August 2020, his group achieved the 1st place at Stanford CheXpert competition. He has published more than 100 papers and served as associate editor of Neurocomputing, and senior PC of AAAI and IJCAI.
After the presentation, there will be a short time for discussion and questions afterwards.
Talks are recorded live via Zoom and are available for viewing later after the talk.