Learning from Imperfect Supervision

Event Date: April 3, 2025
Time: 10:30 AM
Location: MSEE 112
Priority: No
School or Program: Electrical and Computer Engineering
College Calendar: Show
Join Masashi Sugiyama, professor at the University of Tokyo and director of the RIKEN Center for Advanced Intelligence Project, as he speaks on learning from imperfect supervision.

 

In person attendance is highly encouraged. 

Abstract

In many machine learning applications, collecting a large amount of high-quality labeled data is often challenging. However, relying solely on unlabeled data may not always be reliable. To address this issue, leveraging imperfect data presents a promising approach. In this talk, I will provide an overview of our recent research on developing reliable machine learning methods under imperfect supervision. This includes weakly supervised learning, learning with noisy labels, and transfer learning. Finally, I will discuss how machine learning research should evolve in the era of large foundation models. 

Bio

Masashi Sugiyama received his Ph.D. in Computer Science from Tokyo Institute of Technology, Japan, in 2001. After serving as an assistant and associate professor at the same institute, he became a professor at the University of Tokyo in 2014. Since 2016, he has also served as the director of the RIKEN Center for Advanced Intelligence Project. His research interests include theories and algorithms of machine learning. He was awarded the Japan Academy Medal in 2017 and the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology of Japan in 2022. 

 

Host

Assistant Professor Xiaoquian (Joy) Wang, joywang@purdue.edu, 765-494-2045
 

Zoom link: https://purdue-edu.zoom.us/j/99029519791 Meeting ID: 990 2951 9791

2025-04-03 10:30:00 2025-04-03 11:30:00 America/Indiana/Indianapolis Learning from Imperfect Supervision Join Masashi Sugiyama, professor at the University of Tokyo and director of the RIKEN Center for Advanced Intelligence Project, as he speaks on learning from imperfect supervision. MSEE 112 Add to Calendar