Aravindan Vijayaraghavan, Northwestern University, Sivaraman Balakrishnan, Carnegie Mellon University
Principled Approaches for Learning with Test-time Robustness
Cho-Jui Hsieh, University of California, Los Angeles
Scalability and Tunability for Neural Network Optimizers
Golnoosh Farnadi, University of Montreal, HEC Montreal/MILA
Addressing Algorithmic Fairness in Decision-focused Deep Learning
Harrie Oosterhuis, Radboud University
Search and Recommendation Systems that Learn from Diverse User Preferences
Jimmy Ba, University of Toronto
Model-based Reinforcement Learning with Causal World Models
Nadav Cohen, Tel-Aviv University
A Dynamical Theory of Deep Learning
Nihar Shah, Carnegie Mellon University
Addressing Unfairness in Distributed Human Decisions
Nima Fazeli, University of Michigan
Semi-Implicit Methods for Deformable Object Manipulation
Qingyao Ai, University of Utah
Metric-agnostic Ranking Optimization
Stefanie Jegelka, Massachusetts Institute of Technology
Generalization of Graph Neural Networks under Distribution Shifts
Virginia Smith, Carnegie Mellon University
A Multi-Task Approach for Trustworthy Federated Learning