| Cluster-gcn: An efficient algorithm for training deep and large graph convolutional networks WL Chiang, X Liu, S Si, Y Li, S Bengio, CJ Hsieh Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019 | 1238 | 2019 |
| Towards robust neural networks via random self-ensemble X Liu, M Cheng, H Zhang, CJ Hsieh Proceedings of the european conference on computer vision (ECCV), 369-385, 2018 | 481 | 2018 |
| Adv-bnn: Improved adversarial defense through robust bayesian neural network X Liu, Y Li, C Wu, CJ Hsieh arXiv preprint arXiv:1810.01279, 2018 | 198 | 2018 |
| Rob-gan: Generator, discriminator, and adversarial attacker X Liu, CJ Hsieh Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 112 | 2019 |
| Learning to encode position for transformer with continuous dynamical model X Liu, HF Yu, I Dhillon, CJ Hsieh International conference on machine learning, 6327-6335, 2020 | 106 | 2020 |
| Neural sde: Stabilizing neural ode networks with stochastic noise X Liu, T Xiao, S Si, Q Cao, S Kumar, CJ Hsieh arXiv preprint arXiv:1906.02355, 2019 | 99 | 2019 |
| A unified framework for data poisoning attack to graph-based semi-supervised learning X Liu, S Si, X Zhu, Y Li, CJ Hsieh arXiv preprint arXiv:1910.14147, 2019 | 89 | 2019 |
| Gradient boosting neural networks: Grownet S Badirli, X Liu, Z Xing, A Bhowmik, K Doan, SS Keerthi arXiv preprint arXiv:2002.07971, 2020 | 76 | 2020 |
| Evaluations and methods for explanation through robustness analysis CY Hsieh, CK Yeh, X Liu, P Ravikumar, S Kim, S Kumar, CJ Hsieh arXiv preprint arXiv:2006.00442, 2020 | 51 | 2020 |
| How does noise help robustness? explanation and exploration under the neural sde framework X Liu, T Xiao, S Si, Q Cao, S Kumar, CJ Hsieh Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 51 | 2020 |
| Si Si, Qin Cao, Sanjiv Kumar, and Cho-Jui Hsieh. Neural sde: Stabilizing neural ode networks with stochastic noise X Liu, T Xiao arXiv preprint arXiv:1906.02355 2, 2019 | 46 | 2019 |
| Graphdefense: Towards robust graph convolutional networks X Wang, X Liu, CJ Hsieh arXiv preprint arXiv:1911.04429, 2019 | 31 | 2019 |
| Investigating heterogeneities of live mesenchymal stromal cells using AI-based label-free imaging S Imboden, X Liu, BS Lee, MC Payne, CJ Hsieh, NYC Lin Scientific Reports 11 (1), 6728, 2021 | 26 | 2021 |
| Evaluating the robustness of nearest neighbor classifiers: A primal-dual perspective L Wang, X Liu, J Yi, ZH Zhou, CJ Hsieh arXiv preprint arXiv:1906.03972, 2019 | 21 | 2019 |
| Improving the speed and quality of gan by adversarial training J Zhong, X Liu, CJ Hsieh arXiv preprint arXiv:2008.03364, 2020 | 20 | 2020 |
| An inexact subsampled proximal Newton-type method for large-scale machine learning X Liu, CJ Hsieh, JD Lee, Y Sun arXiv preprint arXiv:1708.08552, 2017 | 15 | 2017 |
| From adversarial training to generative adversarial networks X Liu, CJ Hsieh | 13 | 2018 |
| Stochastic second-order methods for non-convex optimization with inexact Hessian and gradient L Liu, X Liu, CJ Hsieh, D Tao arXiv preprint arXiv:1809.09853, 2018 | 13 | 2018 |
| Label disentanglement in partition-based extreme multilabel classification X Liu, WC Chang, HF Yu, CJ Hsieh, I Dhillon Advances in Neural Information Processing Systems 34, 15359-15369, 2021 | 12 | 2021 |
| Fast variance reduction method with stochastic batch size X Liu, CJ Hsieh International Conference on Machine Learning, 3179-3188, 2018 | 7 | 2018 |
Cho-Jui HsiehUniversity of California, Los AngelesVerified email at cs.ucla.edu
