Timetable for the TrustML YSS online seminars from Jan. to Feb., 2023.

Time (JST)Time (Your Browser)TitleSpeaker Video Link

11:00-12:00 03/03/2023


Economic Modeling, Decision-Making, and Mechanism Design using the AI Economist:
Stephan Zheng (Salesforce Research)
Video

17:00-18:00 10/03/2023


Learning Efficiently from Data using Sparse Neural Networks:
Zahra Atashgahi (University of Twente)
Video

18:00-19:00 10/03/2023


Generative Computer Vision: Robust Generalization with Analysis-by-Synthesis:
Adam Kortylewski (Max Planck Institute for Informatics)
Video

09:00-10:00 17/03/2023


A data-centric view on reliable generalization: From ImageNet to LAION-5B
Ludwig Schmidt (U Washington)
Video

10:00-11:00 24/03/2023


ML Safety
Dan Hendrycks (UC Berkeley)
Video

09:00-10:00 27/03/2023


Provable Domain Generalization via Invariant-Feature Subspace Recovery:
Han Zhao (University of Illinois at Urbana-Champaign)
Video

10:00-11:00 27/03/2023


Great Haste Makes Great Waste: Exploiting and Attacking Efficient Deep Learning
Sanghyun Hong (Oregon State University)
Video

10:00-11:00 28/03/2023


Netflix and Forget:
Mimee Xu (New York University)
Video

18:00-19:00 29/03/2023


Imitation Attacks and Defenses:
Xuanli He (University College London)
Video

11:00-12:00 30/03/2023


Global Optimization with Parametric Function Approximation:
Chong Liu (UC Santa Barbara)
Video

10:00-11:00 04/04/2023


Biologically Inspired Foveation Filter Improves Robustness to Adversarial Attacks:
Muhammad Ahmed Shah (Carnegie Mellon University)
Video

17:00-18:00 18/04/2023


Adversarial Attacks for Tabular Data: Application to Fraud Detection and Imbalanced Data:
Yuki Funabiki (Sony Group Corporation JAPAN)
Video

10:00-11:00 20/04/2023


The Vulnerabilities of Preprocessing in Adversarial Machine Learning:
Yue Gao (University of Wisconsin at Madison)
Video

11:00-12:00 20/04/2023


Towards Sample-Optimal Offline Reinforcement Learning:
Ming Yin (UC Santa Barbara)
Video