Runtian Zhai
Runtian Zhai
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Adversarially Robust Generalization Just Requires More Unlabeled Data
R Zhai, T Cai, D He, C Dan, K He, J Hopcroft, L Wang
arXiv preprint arXiv:1906.00555, 2019
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius
R Zhai, C Dan, D He, H Zhang, B Gong, P Ravikumar, CJ Hsieh, L Wang
ICLR 2020, 2020
DORO: Distributional and Outlier Robust Optimization
R Zhai, C Dan, JZ Kolter, P Ravikumar
ICML 2021, 2021
Transferred Discrepancy: Quantifying the Difference Between Representations
Y Feng, R Zhai, D He, L Wang, B Dong
arXiv preprint arXiv:2007.12446, 2020
Understanding Why Generalized Reweighting Does Not Improve Over ERM
R Zhai, C Dan, Z Kolter, P Ravikumar
ICLR 2023, 2022
Boosted CVaR Classification
R Zhai, C Dan, AS Suggala, Z Kolter, P Ravikumar
NeurIPS 2021, 2021
Pretrain-to-Finetune Adversarial Training via Sample-wise Randomized Smoothing
L Wang, R Zhai, D He, L Wang, L Jian
Predicting Out-of-Distribution Error with Confidence Optimal Transport
Y Lu, Z Wang, R Zhai, S Kolouri, J Campbell, K Sycara
ICLR 2023 Trustworthy ML Workshop, 2023
Online Continual Learning for Progressive Distribution Shift (OCL-PDS): A Practitioner's Perspective
R Zhai, S Schroedl, A Galstyan, A Kumar, G Ver Steeg, P Natarajan
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