DaST: Data-Free Substitute Training for Adversarial Attacks. - Mingyi Zhou; Jing Wu 021; Yipeng Liu 001; Shuaicheng Liu; Ce Zhu (CVPR, 2020)

Adversarial Imitation Attack. - Mingyi Zhou; Jing Wu 021; Yipeng Liu 001; Xiaolin Huang; Shuaicheng Liu; Xiang Zhang 006; Ce Zhu (CoRR, 2020)

ProbaNet: Proposal-balanced Network for Object Detection. - Jing Wu 021; Xiang Zhang 006; Mingyi Zhou; Ce Zhu (CoRR, 2020)

Decision-based Universal Adversarial Attack. - Jing Wu 021; Mingyi Zhou; Shuaicheng Liu; Yipeng Liu 001; Ce Zhu (CoRR, 2020)

Performance Evaluation of Adversarial Attacks: Discrepancies and Solutions. - Jing Wu 021; Mingyi Zhou; Ce Zhu; Yipeng Liu 001; Mehrtash Harandi; Li Li 029 (CoRR, 2021)

Defense against Privacy Leakage in Federated Learning. - Jing Wu 021; Munawar Hayat; Mingyi Zhou; Mehrtash Harandi (CoRR, 2022)

ModelObfuscator: Obfuscating Model Information to Protect Deployed ML-Based Systems. - Mingyi Zhou; Xiang Gao 012; Jing Wu 021; John C. Grundy; Xiao Chen 002; Chunyang Chen 001; Li Li 029 (ISSTA, 2023)

Concealing Sensitive Samples against Gradient Leakage in Federated Learning. - Jing Wu 021; Munawar Hayat; Mingyi Zhou; Mehrtash Harandi (AAAI, 2024)

Scissorhands: Scrub Data Influence via Connection Sensitivity in Networks. - Jing Wu 021; Mehrtash Harandi (ECCV (47), 2024)

Investigating White-Box Attacks for On-Device Models. - Mingyi Zhou; Xiang Gao 012; Jing Wu 021; Kui Liu 001; Hailong Sun 001; Li Li 029 (ICSE, 2024)

EraseDiff: Erasing Data Influence in Diffusion Models. - Jing Wu 021; Trung Le 001; Munawar Hayat; Mehrtash Harandi (CoRR, 2024)

MUNBa: Machine Unlearning via Nash Bargaining. - Jing Wu 021; Mehrtash Harandi (CoRR, 2024)

Analyzing the pregnancy status of giant pandas with hierarchical behavioral information. - Xianggang Li; Jing Wu 021; Rong Hou; Zhangyu Zhou; Chang Duan; Peng Liu; Mengnan He; Yingjie Zhou; Peng Chen; Ce Zhu (Expert Syst. Appl., 2024)

Erasing Undesirable Influence in Diffusion Models. - Jing Wu 021; Trung Le 001; Munawar Hayat; Mehrtash Harandi (CVPR, 2025)