70 citations · 141 across the 3 of their papers we have counts for
6 papers
Learning Invariant Representations across Domains and Tasks
Jindong Wang, Wenjie Feng, Chang Liu +5
Being expensive and time-consuming to collect massive COVID-19 image samples to train deep classification models, transfer learning is a promising approach by transferring knowledg…
Free-riders in Federated Learning: Attacks and Defenses
Jierui Lin, Min Du, Jian Liu
Federated learning is a recently proposed paradigm that enables multiple clients to collaboratively train a joint model. It allows clients to train models locally, and leverages th…
Robust Anomaly Detection and Backdoor Attack Detection Via Differential Privacy
Min Du, Ruoxi Jia, Dawn Song
Outlier detection and novelty detection are two important topics for anomaly detection. Suppose the majority of a dataset are drawn from a certain distribution, outlier detection a…
Time-aware Gradient Attack on Dynamic Network Link Prediction
Jinyin Chen, Jian Zhang, Zhi Chen +2
In network link prediction, it is possible to hide a target link from being predicted with a small perturbation on network structure. This observation may be exploited in many real…
TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems
Wenbo Guo, Lun Wang, Xinyu Xing +2
A trojan backdoor is a hidden pattern typically implanted in a deep neural network. It could be activated and thus forces that infected model behaving abnormally only when an input…
Curriculum Adversarial Training
Qi-Zhi Cai, Min Du, Chang Liu +1
Recently, deep learning has been applied to many security-sensitive applications, such as facial authentication. The existence of adversarial examples hinders such applications. Th…