4 citations · 5 across the 2 of their papers we have counts for
11 papers
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…
Joint Embedding of Meta-Path and Meta-Graph for Heterogeneous Information Networks
Lichao Sun, Lifang He, Zhipeng Huang +4
Meta-graph is currently the most powerful tool for similarity search on heterogeneous information networks,where a meta-graph is a composition of meta-paths that captures the compl…
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…
Not Just Privacy: Improving Performance of Private Deep Learning in Mobile Cloud
Ji Wang, Jianguo Zhang, Weidong Bao +3
The increasing demand for on-device deep learning services calls for a highly efficient manner to deploy deep neural networks (DNNs) on mobile devices with limited capacity. The cl…
dpMood: Exploiting Local and Periodic Typing Dynamics for Personalized Mood Prediction
He Huang, Bokai Cao, Philip S. Yu +2
Mood disorders are common and associated with significant morbidity and mortality. Early diagnosis has the potential to greatly alleviate the burden of mental illness and the ever…
Multi-View Multi-Graph Embedding for Brain Network Clustering Analysis
Ye Liu, Lifang He, Bokai Cao +3
Network analysis of human brain connectivity is critically important for understanding brain function and disease states. Embedding a brain network as a whole graph instance into a…