Timetable for the TrustML YSS online seminars from Jul to Aug., 2022.

Time (JST)	Time (Your Browser)	Title	Speaker	Video Link
10:00-11:00 05/07/2022		Toward a Principled Understanding of Robust Machine Learning Methods and Its Connection to Multiple Aspects: Haohan Wang (Carnegie Mellon University)		Video
9:00-10:00 08/07/2022		Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization: Junyuan Hong (Michigan State University)		Video
11:00-12:00 20/07/2022		Learning and Using Causal Knowledge: A Further Step Towards a Higher-Level Intelligence: Biwei Huang (Carnegie Mellon University)		Video
15:30-16:30 26/07/2022		Deep Learning for Biosequences: Jean-Philippe Vert (Google Research)		Video
10:00-11:00 08/08/2022		The Matthew Effect when Learning from Weakly Supervised Data: Yang Liu (UCSC)		Video
9:00-10:00 16/08/2022		A Learning-Theoretic Framework for Certified Auditing of Machine Learning Models: Chhavi Yadav (UCSD)		Video
10:00-11:00 16/08/2022		Understanding Pre-Training, Fine-Tuning, and Self-Training for Unsupervised Domain Adaptation: Ananya Kumar (Stanford University)		Video
10:00-11:00 24/08/2022		Enabling Large-Scale Certifiable Deep Learning towards Trustworthy Machine Learning: Linyi Li (UIUC)		Video