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 | 147 | 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 | 86 | 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 | 46 | 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 | 45* | 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 | 28 | 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 | 27 | 2020 |
Cost-Sensitive Robustness against Adversarial Examples X Zhang, D Evans International Conference on Learning Representations (ICLR), 2019, 2019 | 25 | 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 | 25* | 2017 |
Robust wirtinger flow for phase retrieval with arbitrary corruption J Chen, L Wang, X Zhang, Q Gu arXiv preprint arXiv:1704.06256, 2017 | 24 | 2017 |
Empirically measuring concentration: Fundamental limits on intrinsic robustness S Mahloujifar, X Zhang, M Mahmoody, D Evans NeurIPS 2019, 2019 | 23 | 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 |
A unified framework for low-rank plus sparse matrix recovery X Zhang, L Wang, Q Gu arXiv preprint arXiv:1702.06525, 2017 | 6 | 2017 |
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 | 5 | 2021 |
Understanding Intrinsic Robustness using Label Uncertainty X Zhang, D Evans International Conference on Learning Representations (ICLR), 2022, 2022 | 4* | 2022 |
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 | 1 | 2023 |
AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks Y Zeng, Y Wu, X Zhang, H Wang, Q Wu arXiv preprint arXiv:2403.04783, 2024 | | 2024 |
Generating Less Certain Adversarial Examples Improves Robust Generalization M Zhang, M Backes, X Zhang arXiv preprint arXiv:2310.04539, 2023 | | 2023 |
Provably Robust Cost-Sensitive Learning via Randomized Smoothing Y Xin, M Backes, X Zhang The Second Workshop on New Frontiers in Adversarial Machine Learning, 2023 | | 2023 |
From Characterizing Intrinsic Robustness to Adversarially Robust Machine Learning X Zhang University of Virginia, 2022 | | 2022 |