Sep-Oct 2022
Timetable for the TrustML YSS online seminars from Sep to Oct., 2022.
Time (JST)
Time (Your Browser)
Title
Speaker
Video Link
11:00-12:00 01/09/2022
Predicting Out-of-Distribution Error with the Projection Norm:
Yaodong Yu (University of California, Berkeley)
Video
10:00-11:00 02/09/2022
Understanding Dataset Difficulty with V-Usable Information:
Kawin Ethayarajh (Stanford University)
Video
15:00-16:00 02/09/2022
On the Impact of Estimating Example Difficulty:
Chirag Agarwal (Adobe)
Video
9:00-10:00 06/09/2022
Understanding Probability Estimation and Noisy Label Learning: From the Early Learning Perspective:
Sheng Liu (New York University)
Video
9:00-10:00 16/09/2022
Provably calibrating ML classifiers without distributional assumptions:
Chirag Gupta (Carnegie Mellon University)
Video
10:00-11:00 16/09/2022
Humanly Certify Superhuman Classifiers:
Qiongkai Xu (University of Melbourne)
No video
14:30-15:30 16/09/2022
Recent Advances in Domain Adaptation and Generalization:
Mahsa Baktashmotlagh (University of Queensland)
Video
10:00-11:00 06/10/2022
Challenges and Opportunities in Out-of-distribution Detection:
Sharon Y. Li (University of Wisconsin Madison)
Video
10:00-11:00 19/10/2022
Online Adaptation to Label Distribution Shift:
Ruihan Wu (Cornell University)
Video
15:00-16:00 26/10/2022
A Framework of Weakly Supervised Learning by Semi-Supervised Learning:
Zhuowei Wang (Commonwealth Scientific and Industrial Research Organization, Australia)
Video
16:00-17:00 26/10/2022
Statistical Aspects of Trustworthy Machine Learning
Nikola Konstantinov (ETH AI Center)
Video
16:00-17:00 28/10/2022
Explainable Artificial Intelligence: Academic Research and Industrial Applications in Korea
Jaesik Choi (KAIST)
Video
11:00-12:00 31/10/2022
Toward Efficient Evaluation and Training of Adversarially Robust Neural Networks:
Gaurang Sriramanan (University of Maryland)
Video
14:00-15:00 31/10/2022
A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search:
Tuan Dam (TU Darmstadt)
Video
