12 citations · 13 across the 2 of their papers we have counts for
6 papers
An Embarrassingly Simple Approach for Trojan Attack in Deep Neural Networks
Ruixiang Tang, Mengnan Du, Ninghao Liu +2
With the widespread use of deep neural networks (DNNs) in high-stake applications, the security problem of the DNN models has received extensive attention. In this paper, we invest…
Towards Generalizable Deepfake Detection with Locality-aware AutoEncoder
Mengnan Du, Shiva Pentyala, Yuening Li +1
With advancements of deep learning techniques, it is now possible to generate super-realistic images and videos, i.e., deepfakes. These deepfakes could reach mass audience and resu…
Evaluating Explanation Without Ground Truth in Interpretable Machine Learning
Fan Yang, Mengnan Du, Xia Hu
Interpretable Machine Learning (IML) has become increasingly important in many real-world applications, such as autonomous cars and medical diagnosis, where explanations are signif…
Learning Credible Deep Neural Networks with Rationale Regularization
Mengnan Du, Ninghao Liu, Fan Yang +1
Recent explainability related studies have shown that state-of-the-art DNNs do not always adopt correct evidences to make decisions. It not only hampers their generalization but al…
Deep Structured Cross-Modal Anomaly Detection
Yuening Li, Ninghao Liu, Jundong Li +2
Anomaly detection is a fundamental problem in data mining field with many real-world applications. A vast majority of existing anomaly detection methods predominately focused on da…
On Attribution of Recurrent Neural Network Predictions via Additive Decomposition
Mengnan Du, Ninghao Liu, Fan Yang +2
RNN models have achieved the state-of-the-art performance in a wide range of text mining tasks. However, these models are often regarded as black-boxes and are criticized due to th…