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Contributed Talk: DensePure: Understanding Diffusion Models towards Adversarial Robustness
Zhongzhu Chen · Kun Jin · Jiongxiao Wang · Weili Nie · Mingyan Liu · Anima Anandkumar · Bo Li · Dawn Song

Fri Dec 09 01:30 PM -- 01:40 PM (PST) @
in Trustworthy and Socially Responsible Machine Learning »

Author Information

Zhongzhu Chen (University of Michigan)
Kun Jin (University of Michigan, Ann Arbor)
Jiongxiao Wang (Arizona State University)
Weili Nie (NVIDIA)
Mingyan Liu (University of Michigan, Ann Arbor)

Mingyan Liu (M'00, SM'11, F'14) received her Ph.D. Degree in electrical engineering from the University of Maryland, College Park, in 2000. She is currently a professor with the Department of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor, and the Peter and Evelyn Fuss Chair of Electrical and Computer Engineering. Her research interests are in optimal resource allocation, performance modeling, sequential decision and learning theory, game theory and incentive mechanisms, with applications to large-scale networked systems, cybersecurity and cyber risk quantification. She has served on the editorial boards of IEEE/ACM Trans. Networking, IEEE Trans. Mobile Computing, and ACM Trans. Sensor Networks. She is a Fellow of the IEEE and a member of the ACM.

Anima Anandkumar (NVIDIA / Caltech)
Bo Li (UIUC)
Dawn Song (UC Berkeley)

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