293 citations · 349 across the 7 of their papers we have counts for
7 papers
Not Just Cloud Privacy: Protecting Client Privacy in Teacher-Student Learning
Lichao Sun, Ji Wang, Philip S. Yu +1
Ensuring the privacy of sensitive data used to train modern machine learning models is of paramount importance in many areas of practice. One recent popular approach to study these…
Private Deep Learning with Teacher Ensembles
Lichao Sun, Yingbo Zhou, Ji Wang +4
Privacy-preserving deep learning is crucial for deploying deep neural network based solutions, especially when the model works on data that contains sensitive information. Most pri…
Adversarial Attack and Defense on Graph Data: A Survey
Lichao Sun, Yingtong Dou, Carl Yang +5
Deep neural networks (DNNs) have been widely applied to various applications, including image classification, text generation, audio recognition, and graph data analysis. However,…
Private Model Compression via Knowledge Distillation
Ji Wang, Weidong Bao, Lichao Sun +3
The soaring demand for intelligent mobile applications calls for deploying powerful deep neural networks (DNNs) on mobile devices. However, the outstanding performance of DNNs noto…
Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction
Jianguo Zhang, Ji Wang, Lifang He +2
With the development of cloud computing and big data, the reliability of data storage systems becomes increasingly important. Previous researchers have shown that machine learning…
Deep Learning Towards Mobile Applications
Ji Wang, Bokai Cao, Philip S. Yu +3
Recent years have witnessed an explosive growth of mobile devices. Mobile devices are permeating every aspect of our daily lives. With the increasing usage of mobile devices and in…