| Learning one-hidden-layer relu networks via gradient descent X Zhang, Y Yu, L Wang, Q Gu International Conference on Artificial Intelligence and Statistics (AISTATS …, 2019 | 154 | 2019 |
| A unified computational and statistical framework for nonconvex low-rank matrix estimation L Wang, X Zhang, Q Gu International Conference on Artificial Intelligence and Statistics (AISTATS …, 2017 | 89 | 2017 |
| A primal-dual analysis of global optimality in nonconvex low-rank matrix recovery X Zhang, L Wang, Y Yu, Q Gu International Conference on Machine Learning (ICML), 2018, 2018 | 47 | 2018 |
| A unified framework for nonconvex low-rank plus sparse matrix recovery X Zhang, LW Wang, Q Gu International Conference on Artificial Intelligence and Statistics (AISTATS …, 2018 | 46* | 2018 |
| Fast and sample efficient inductive matrix completion via multi-phase procrustes flow X Zhang, SS Du, Q Gu International Conference on Machine Learning (ICML), 2018, 2018 | 29 | 2018 |
| Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization S Zhu, X Zhang, D Evans International Conference on Machine Learning (ICML), 2020, 2020 | 26 | 2020 |
| Cost-Sensitive Robustness against Adversarial Examples X Zhang, D Evans International Conference on Learning Representations (ICLR), 2019, 2019 | 26 | 2019 |
| A unified variance reduction-based framework for nonconvex low-rank matrix recovery L Wang, X Zhang, Q Gu International Conference on Machine Learning (ICML), 2017, 2017 | 26* | 2017 |
| Robust wirtinger flow for phase retrieval with arbitrary corruption J Chen, L Wang, X Zhang, Q Gu arXiv preprint arXiv:1704.06256, 2017 | 25 | 2017 |
| Empirically measuring concentration: Fundamental limits on intrinsic robustness S Mahloujifar, X Zhang, M Mahmoody, D Evans NeurIPS 2019, 2019 | 24 | 2019 |
| Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models X Zhang, J Chen, Q Gu, D Evans International Conference on Artificial Intelligence and Statistics (AISTATS …, 2020 | 16 | 2020 |
| Autodefense: Multi-agent llm defense against jailbreak attacks Y Zeng, Y Wu, X Zhang, H Wang, Q Wu arXiv preprint arXiv:2403.04783, 2024 | 15 | 2024 |
| Understanding Intrinsic Robustness using Label Uncertainty X Zhang, D Evans International Conference on Learning Representations (ICLR), 2022, 2022 | 8* | 2022 |
| Improved Estimation of Concentration under Lp-norm Distance Metrics using Half Spaces JB Prescott, X Zhang, D Evans International Conference on Learning Representations (ICLR) 2021, 2021 | 7 | 2021 |
| A unified framework for low-rank plus sparse matrix recovery X Zhang, L Wang, Q Gu arXiv preprint arXiv:1702.06525, 2017 | 6 | 2017 |
| What Distributions are Robust to Indiscriminate Poisoning Attacks for Linear Learners? F Suya, X Zhang, Y Tian, D Evans Advances in neural information processing systems (NeurIPS 2023) 36, 2023 | 3* | 2023 |
| Transferable availability poisoning attacks Y Liu, M Backes, X Zhang arXiv preprint arXiv:2310.05141, 2023 | 3 | 2023 |
| Generating Less Certain Adversarial Examples Improves Robust Generalization M Zhang, M Backes, X Zhang arXiv preprint arXiv:2310.04539, 2023 | 1 | 2023 |
| Improving the Efficiency of Self-Supervised Adversarial Training through Latent Clustering-based Selection S Ghosh, Y Xu, X Zhang ICML 2024 Next Generation of AI Safety Workshop, 2024 | | 2024 |
| Understanding Adversarially Robust Generalization via Weight-Curvature Index Y Xu, X Zhang High-dimensional Learning Dynamics 2024: The Emergence of Structure and …, 2024 | | 2024 |
Quanquan GuAssociate Professor of Computer Science, UCLAVerified email at cs.ucla.edu
