| How does mixup help with robustness and generalization? L Zhang, Z Deng, K Kawaguchi, A Ghorbani, J Zou arXiv preprint arXiv:2010.04819, 2020 | 157 | 2020 |
| An unconstrained layer-peeled perspective on neural collapse W Ji, Y Lu, Y Zhang, Z Deng, WJ Su arXiv preprint arXiv:2110.02796, 2021 | 29 | 2021 |
| 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 | 28 | 2021 |
| Toward better generalization bounds with locally elastic stability Z Deng, H He, W Su International Conference on Machine Learning, 2590-2600, 2021 | 24 | 2021 |
| When and how mixup improves calibration L Zhang, Z Deng, K Kawaguchi, J Zou International Conference on Machine Learning, 26135-26160, 2022 | 19 | 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 | 19 | 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 | 16 | 2021 |
| Decision-aware conditional gans for time series data H Sun, Z Deng, H Chen, DC Parkes arXiv preprint arXiv:2009.12682, 2020 | 15 | 2020 |
| 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 | 15 | 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 | 11 | 2020 |
| Scaffolding sets M Burhanpurkar, Z Deng, C Dwork, L Zhang arXiv preprint arXiv:2111.03135, 2021 | 10 | 2021 |
| Interpreting robust optimization via adversarial influence functions Z Deng, C Dwork, J Wang, L Zhang International Conference on Machine Learning, 2464-2473, 2020 | 10 | 2020 |
| Understanding dynamics of nonlinear representation learning and its application K Kawaguchi, L Zhang, Z Deng Neural computation 34 (4), 991-1018, 2022 | 9 | 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 | 5 | 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 | 5 | 2022 |
| How Does Mixup Help With Robustness and Generalization? arXiv 2021 L Zhang, Z Deng, K Kawaguchi, A Ghorbani, JY Zou arXiv preprint arXiv:2010.04819, 2010 | 5 | 2010 |
| Understanding multimodal contrastive learning and incorporating unpaired data R Nakada, HI Gulluk, Z Deng, W Ji, J Zou, L Zhang International Conference on Artificial Intelligence and Statistics, 4348-4380, 2023 | 3 | 2023 |
| HappyMap: A Generalized Multi-calibration Method Z Deng, C Dwork, L Zhang arXiv preprint arXiv:2303.04379, 2023 | 3 | 2023 |
| 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 | 3 | 2021 |
| Reinforcement Learning with Stepwise Fairness Constraints Z Deng, H Sun, ZS Wu, L Zhang, DC Parkes arXiv preprint arXiv:2211.03994, 2022 | 1 | 2022 |
Linjun ZhangAssistant Professor of Statistics, Rutgers UniversityVerified email at rutgers.edu
