2 citations · 5 across the 4 of their papers we have counts for
4 papers
Decoupling the Class Label and the Target Concept in Machine Unlearning
Jianing Zhu, Bo Han, Jiangchao Yao +3
Machine unlearning as an emerging research topic for data regulations, aims to adjust a trained model to approximate a retrained one that excludes a portion of training data. Previ…
From Large Language Models to Databases and Back: A discussion on research and education
Sihem Amer-Yahia, Angela Bonifati, Lei Chen +4
This discussion was conducted at a recent panel at the 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023), held April 17-20, 2023 in Tianjin,…
Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability
Jianing Zhu, Hengzhuang Li, Jiangchao Yao +3
Out-of-distribution (OOD) detection is an indispensable aspect of secure AI when deploying machine learning models in real-world applications. Previous paradigms either explore bet…
Combating Exacerbated Heterogeneity for Robust Models in Federated Learning
Jianing Zhu, Jiangchao Yao, Tongliang Liu +3
Privacy and security concerns in real-world applications have led to the development of adversarially robust federated models. However, the straightforward combination between adve…