Publications

Jia Fu, Xiao Zhang, Sepideh Pashami, Fatemeh Rahimian, Anders Holst (2024). DiffPAD: Denoising Diffusion-based Adversarial Patch Decontamination. WACV 2025.

Minxing Zhang, Michael Backes, Xiao Zhang (2024). Generating Less Certain Adversarial Examples Improves Robust Generalization. Transactions on Machine Learning Research (TMLR).

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Santanu Rathod, Pietro Liò, Xiao Zhang (2024). Predicting Time-varying Flux and Balance in Metabolic Systems using Structured Neural ODE Processes. ArXiv.

Minxing Zhang, Michael Backes, Xiao Zhang (2024). Invisibility Cloak: Disappearance under Human Pose Estimation via Backdoor Attacks. ArXiv.

Somrita Ghosh, Yuelin Xu, Xiao Zhang (2024). Improving the Efficiency of Self-Supervised Adversarial Training through Latent Clustering-based Selection. ICML 2024 NextGenAISafety Workshop.

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Yuelin Xu, Xiao Zhang (2024). Understanding Adversarially Robust Generalization via Weight-Curvature Index. ICML 2024 HiLD Workshop.

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Anshuman Suri, Xiao Zhang, David Evans (2024). Do Parameters Reveal More than Loss for Membership Inference?. ICML 2024 HiLD Workshop.

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Wenshu Fan, Hongwei Li, Wenbo Jiang, Meng Hao, Shui Yu, Xiao Zhang (2024). Stealthy Targeted Backdoor Attacks against Image Captioning. TIFS.

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Yifan Zeng, Yiran Wu, Xiao Zhang, Huazheng Wang, Qingyun Wu (2024). AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks. ArXiv.

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Fnu Suya, Xiao Zhang, Yuan Tian, David Evans (2023). What Distributions are Robust to Indiscriminate Poisoning Attacks for Linear Learners?. NeurIPS 2023.

Yuan Xin, Michael Backes, Xiao Zhang (2023). Provably Robust Cost-Sensitive Learning via Randomized Smoothing. ArXiv.

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Yiyong Liu, Michael Backes, Xiao Zhang (2023). Transferable Availability Poisoning Attacks. ArXiv.

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Xiao Zhang, David Evans (2022). Understanding Intrinsic Robustness using Label Uncertainty. ICLR 2022.

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Xiao Zhang, David Evans (2021). Incorporating Label Uncertainty in Intrinsic Robustness Measures. ICLR 2021 aisecure workshop.

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Jack Prescott, Xiao Zhang, David Evans (2021). Improved Estimation of Concentration Under Lp-Norm Distance Metric Using Half Spaces. ICLR 2021.

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Xiao Zhang, Jinghui Chen, Quanquan Gu, David Evans (2020). Understanding the intrinsic robustness of image distributions using conditional generative models. AISTATS 2020.

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Sicheng Zhu, Xiao Zhang, David Evans (2020). Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization. ICML 2020.

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Saeed Mahloujifar, Xiao Zhang, Mohammad Mahmoody, David Evans (2019). Empirically Measuring Concentration: Fundamental Limits to Intrinsic Robustness. NeurIPS 2019 (Spotlight).

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Xiao Zhang, David Evans (2019). Cost-Sensitive Robustness against Adversarial Examples. ICLR 2019.

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Xiao Zhang, Yaodong Yu, Lingxiao Wang, Quanquan Gu (2019). Learning One-hidden-layer ReLU Networks via Gradient Descent. AISTATS 2019.

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Xiao Zhang, Simon Du, Quanquan Gu (2018). Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow. ICML 2018.

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Xiao Zhang, Lingxiao Wang, Yaodong Yu, Quanquan Gu (2018). A Primal-Dual Analysis of Global Optimality in Nonconvex Low-Rank Matrix Recovery. ICML 2018.

Xiao Zhang, Lingxiao Wang, Quanquan Gu (2018). A Unified Framework for Nonconvex Low-rank plus Sparse Matrix Recovery. AISTATS 2018.

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Lingxiao Wang, Xiao Zhang, Quanquan Gu (2017). A Unified Variance Reduction-Based Framework for Nonconvex Low-Rank Matrix Recovery. ICML 2017.

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Jinghui Chen, Lingxiao Wang, Xiao Zhang, Quanquan Gu (2017). Robust Wirtinger Flow for Phase Retrieval with Arbitrary Corruption. ArXiv.

Lingxiao Wang, Xiao Zhang, Quanquan Gu (2017). A Unified Computational and Statistical Framework for Nonconvex Low-rank Matrix Estimation. AISTATS 2017.

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