Wenxin Ding

202020212022202320241 5 7 11 18

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Ben Y. ZhaoNeubauer Professor of Computer Science, University of ChicagoAdresse e-mail validée de uchicago.edu
Haitao ZhengNeubauer Professor of Computer Science, University of ChicagoAdresse e-mail validée de cs.uchicago.edu
Shawn ShanUniversity of ChicagoAdresse e-mail validée de cs.uchicago.edu
Nihar B. ShahML and CS departments, Carnegie Mellon UniversityAdresse e-mail validée de cs.cmu.edu
Weina WangCarnegie Mellon UniversityAdresse e-mail validée de cs.cmu.edu
Arjun BhagojiResearch Scientist, University of ChicagoAdresse e-mail validée de uchicago.edu

Wenxin Ding

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Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Prompt-specific poisoning attacks on text-to-image generative models S Shan, W Ding, J Passananti, H Zheng, BY Zhao arXiv preprint arXiv:2310.13828, 2023	15	2023
On the privacy-utility tradeoff in peer-review data analysis W Ding, NB Shah, W Wang arXiv preprint arXiv:2006.16385, 2020	12	2020
Post-breach recovery: Protection against white-box adversarial examples for leaked dnn models S Shan, W Ding, E Wenger, H Zheng, BY Zhao Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications …, 2022	9	2022
Calibration with privacy in peer review W Ding, G Kamath, W Wang, NB Shah 2022 IEEE International Symposium on Information Theory (ISIT), 1635-1640, 2022	6	2022
Characterizing the Optimal Loss for Multi-class Classification with a Test-time Attacker S Dai, W Ding, AN Bhagoji, D Cullina, H Zheng, B Zhao, P Mittal Advances in Neural Information Processing Systems 36, 2024	1	2024
Towards Scalable and Robust Model Versioning W Ding, AN Bhagoji, BY Zhao, H Zheng arXiv preprint arXiv:2401.09574, 2024		2024
Lower Bounds on 0-1 Loss for Multi-class Classification with a Test-time Attacker S Dai, W Ding, AN Bhagoji, D Cullina, P Mittal, BY Zhao NeurIPS ML Safety Workshop, 2022		2022
Calibration with Privacy in Peer Review: A Theoretical Study W Ding Google Research, 2021		2021

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