Zhun Deng
Zhun Deng
Postdoctoral Researcher, Columbia University
Verified email at - Homepage
Cited by
Cited by
How does mixup help with robustness and generalization?
L Zhang, Z Deng, K Kawaguchi, A Ghorbani, J Zou
arXiv preprint arXiv:2010.04819, 2020
Adversarial training helps transfer learning via better representations
Z Deng, L Zhang, K Vodrahalli, K Kawaguchi, JY Zou
Advances in Neural Information Processing Systems 34, 25179-25191, 2021
An unconstrained layer-peeled perspective on neural collapse
W Ji, Y Lu, Y Zhang, Z Deng, WJ Su
arXiv preprint arXiv:2110.02796, 2021
Toward better generalization bounds with locally elastic stability
Z Deng, H He, W Su
International Conference on Machine Learning, 2590-2600, 2021
When and how mixup improves calibration
L Zhang, Z Deng, K Kawaguchi, J Zou
International Conference on Machine Learning, 26135-26160, 2022
The power of contrast for feature learning: A theoretical analysis
W Ji, Z Deng, R Nakada, J Zou, L Zhang
arXiv preprint arXiv:2110.02473, 2021
Improving adversarial robustness via unlabeled out-of-domain data
Z Deng, L Zhang, A Ghorbani, J Zou
International Conference on Artificial Intelligence and Statistics, 2845-2853, 2021
Representation via representations: Domain generalization via adversarially learned invariant representations
Z Deng, F Ding, C Dwork, R Hong, G Parmigiani, P Patil, P Sur
arXiv preprint arXiv:2006.11478, 2020
Decision-aware conditional gans for time series data
H Sun, Z Deng, H Chen, DC Parkes
arXiv preprint arXiv:2009.12682, 2020
Towards understanding the dynamics of the first-order adversaries
Z Deng, H He, J Huang, W Su
International Conference on Machine Learning, 2484-2493, 2020
Scaffolding sets
M Burhanpurkar, Z Deng, C Dwork, L Zhang
arXiv preprint arXiv:2111.03135, 2021
Interpreting robust optimization via adversarial influence functions
Z Deng, C Dwork, J Wang, L Zhang
International Conference on Machine Learning, 2464-2473, 2020
Understanding dynamics of nonlinear representation learning and its application
K Kawaguchi, L Zhang, Z Deng
Neural computation 34 (4), 991-1018, 2022
Robustness implies generalization via data-dependent generalization bounds
K Kawaguchi, Z Deng, K Luh, J Huang
International Conference on Machine Learning, 10866-10894, 2022
FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data
Z Deng, J Zhang, L Zhang, T Ye, Y Coley, WJ Su, J Zou
arXiv preprint arXiv:2206.02792, 2022
How shrinking gradient noise helps the performance of neural networks
Z Deng, J Huang, K Kawaguchi
2021 IEEE International Conference on Big Data (Big Data), 1002-1007, 2021
HappyMap: A Generalized Multi-calibration Method
Z Deng, C Dwork, L Zhang
arXiv preprint arXiv:2303.04379, 2023
Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data
R Nakada, HI Gulluk, Z Deng, W Ji, J Zou, L Zhang
arXiv preprint arXiv:2302.06232, 2023
Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions
JC Snell, TP Zollo, Z Deng, T Pitassi, R Zemel
arXiv preprint arXiv:2212.13629, 2022
Reinforcement Learning with Stepwise Fairness Constraints
Z Deng, H Sun, ZS Wu, L Zhang, DC Parkes
arXiv preprint arXiv:2211.03994, 2022
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