8 citations · 37 across the 16 of their papers we have counts for
6 papers
On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation
Zhanke Zhou, Chenyu Zhou, Xuan Li +3
Although powerful graph neural networks (GNNs) have boosted numerous real-world applications, the potential privacy risk is still underexplored. To close this gap, we perform the f…
Class-Balancing Diffusion Models
Yiming Qin, Huangjie Zheng, Jiangchao Yao +2
Diffusion-based models have shown the merits of generating high-quality visual data while preserving better diversity in recent studies. However, such observation is only justified…
Exploring Model Dynamics for Accumulative Poisoning Discovery
Jianing Zhu, Xiawei Guo, Jiangchao Yao +6
Adversarial poisoning attacks pose huge threats to various machine learning applications. Especially, the recent accumulative poisoning attacks show that it is possible to achieve…
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…
Towards Efficient Task-Driven Model Reprogramming with Foundation Models
Shoukai Xu, Jiangchao Yao, Ran Luo +5
Vision foundation models exhibit impressive power, benefiting from the extremely large model capacity and broad training data. However, in practice, downstream scenarios may only s…
Device-Cloud Collaborative Recommendation via Meta Controller
Jiangchao Yao, Feng Wang, Xichen Ding +4
On-device machine learning enables the lightweight deployment of recommendation models in local clients, which reduces the burden of the cloud-based recommenders and simultaneously…