154 citations · 300 across the 16 of their papers we have counts for
12 papers · 1 filter
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…
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…
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…
Broad Learning for Healthcare
Bokai Cao
A broad spectrum of data from different modalities are generated in the healthcare domain every day, including scalar data (e.g., clinical measures collected at hospitals), tensor…
HitFraud: A Broad Learning Approach for Collective Fraud Detection in Heterogeneous Information Networks
Bokai Cao, Mia Mao, Siim Viidu +1
On electronic game platforms, different payment transactions have different levels of risk. Risk is generally higher for digital goods in e-commerce. However, it differs based on p…
Multi-view Unsupervised Feature Selection by Cross-diffused Matrix Alignment
Xiaokai Wei, Bokai Cao, Philip S. Yu
Multi-view high-dimensional data become increasingly popular in the big data era. Feature selection is a useful technique for alleviating the curse of dimensionality in multi-view…
Learning from Multi-View Multi-Way Data via Structural Factorization Machines
Chun-Ta Lu, Lifang He, Hao Ding +2
Real-world relations among entities can often be observed and determined by different perspectives/views. For example, the decision made by a user on whether to adopt an item relie…
Mining Brain Networks using Multiple Side Views for Neurological Disorder Identification
Bokai Cao, Xiangnan Kong, Jingyuan Zhang +2
Mining discriminative subgraph patterns from graph data has attracted great interest in recent years. It has a wide variety of applications in disease diagnosis, neuroimaging, etc.…
A review of heterogeneous data mining for brain disorders
Bokai Cao, Xiangnan Kong, Philip S. Yu
With rapid advances in neuroimaging techniques, the research on brain disorder identification has become an emerging area in the data mining community. Brain disorder data poses ma…
Multi-View Factorization Machines
Bokai Cao, Hucheng Zhou, Guoqiang Li +1
For a learning task, data can usually be collected from different sources or be represented from multiple views. For example, laboratory results from different medical examinations…
Meta Path-Based Collective Classification in Heterogeneous Information Networks
Xiangnan Kong, Bokai Cao, Philip S. Yu +2
Collective classification has been intensively studied due to its impact in many important applications, such as web mining, bioinformatics and citation analysis. Collective classi…