research
∙
06/01/2023
Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation
Good data augmentation is one of the key factors that lead to the empiri...
share
research
∙
05/25/2023
Characterizing Out-of-Distribution Error via Optimal Transport
Out-of-distribution (OOD) data poses serious challenges in deployed mach...
research
∙
02/10/2023
Predicting Out-of-Distribution Error with Confidence Optimal Transport
Out-of-distribution (OOD) data poses serious challenges in deployed mach...
research
∙
01/28/2022
Understanding Why Generalized Reweighting Does Not Improve Over ERM
Empirical risk minimization (ERM) is known in practice to be non-robust ...
research
∙
10/26/2021
Boosted CVaR Classification
Many modern machine learning tasks require models with high tail perform...
research
∙
06/11/2021
DORO: Distributional and Outlier Robust Optimization
Many machine learning tasks involve subpopulation shift where the testin...
research
∙
07/24/2020
Transferred Discrepancy: Quantifying the Difference Between Representations
Understanding what information neural networks capture is an essential p...
research
∙
01/08/2020
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius
Adversarial training is one of the most popular ways to learn robust mod...
research
∙
06/03/2019
