Search Results for author: Bokai Cao

Found 15 papers, 2 papers with code

Private Model Compression via Knowledge Distillation

no code implementations13 Nov 2018 Ji Wang, Weidong Bao, Lichao Sun, Xiaomin Zhu, Bokai Cao, Philip S. Yu

To benefit from the on-device deep learning without the capacity and privacy concerns, we design a private model compression framework RONA.

Knowledge Distillation Model Compression +1

Joint Embedding of Meta-Path and Meta-Graph for Heterogeneous Information Networks

no code implementations11 Sep 2018 Lichao Sun, Lifang He, Zhipeng Huang, Bokai Cao, Congying Xia, Xiaokai Wei, Philip S. Yu

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 complex structural information.

Network Embedding Tensor Decomposition

Deep Learning Towards Mobile Applications

no code implementations10 Sep 2018 Ji Wang, Bokai Cao, Philip S. Yu, Lichao Sun, Weidong Bao, Xiaomin Zhu

In this paper, we provide an overview of the current challenges and representative achievements about pushing deep learning on mobile devices from three aspects: training with mobile data, efficient inference on mobile devices, and applications of mobile deep learning.

BIG-bench Machine Learning

Not Just Privacy: Improving Performance of Private Deep Learning in Mobile Cloud

no code implementations10 Sep 2018 Ji Wang, Jian-Guo Zhang, Weidong Bao, Xiaomin Zhu, Bokai Cao, Philip S. Yu

To benefit from the cloud data center without the privacy risk, we design, evaluate, and implement a cloud-based framework ARDEN which partitions the DNN across mobile devices and cloud data centers.

Privacy Preserving

dpMood: Exploiting Local and Periodic Typing Dynamics for Personalized Mood Prediction

1 code implementation29 Aug 2018 He Huang, Bokai Cao, Philip S. Yu, Chang-Dong Wang, Alex D. Leow

Mood disorders are common and associated with significant morbidity and mortality.

Human-Computer Interaction Computers and Society

Multi-View Multi-Graph Embedding for Brain Network Clustering Analysis

no code implementations19 Jun 2018 Ye Liu, Lifang He, Bokai Cao, Philip S. Yu, Ann B. Ragin, Alex D. Leow

Network analysis of human brain connectivity is critically important for understanding brain function and disease states.

Graph Embedding

DeepMood: Modeling Mobile Phone Typing Dynamics for Mood Detection

no code implementations23 Mar 2018 Bokai Cao, Lei Zheng, Chenwei Zhang, Philip S. Yu, Andrea Piscitello, John Zulueta, Olu Ajilore, Kelly Ryan, Alex D. Leow

The increasing use of electronic forms of communication presents new opportunities in the study of mental health, including the ability to investigate the manifestations of psychiatric diseases unobtrusively and in the setting of patients' daily lives.

Broad Learning for Healthcare

no code implementations23 Mar 2018 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 data (e. g., neuroimages analyzed by research institutes), graph data (e. g., brain connectivity networks), and sequence data (e. g., digital footprints recorded on smart sensors).

Network Embedding

Multi-view Unsupervised Feature Selection by Cross-diffused Matrix Alignment

no code implementations2 May 2017 Xiaokai Wei, Bokai Cao, Philip S. Yu

In this paper, we study unsupervised feature selection for multi-view data, as class labels are usually expensive to obtain.

MULTI-VIEW LEARNING

Learning from Multi-View Multi-Way Data via Structural Factorization Machines

no code implementations10 Apr 2017 Chun-Ta Lu, Lifang He, Hao Ding, Bokai Cao, Philip S. Yu

Real-world relations among entities can often be observed and determined by different perspectives/views.

Mining Brain Networks using Multiple Side Views for Neurological Disorder Identification

no code implementations19 Aug 2015 Bokai Cao, Xiangnan Kong, Jingyuan Zhang, Philip S. Yu, Ann B. Ragin

In this paper, we study the problem of discriminative subgraph selection using multiple side views and propose a novel solution to find an optimal set of subgraph features for graph classification by exploring a plurality of side views.

General Classification Graph Classification

A review of heterogeneous data mining for brain disorders

no code implementations5 Aug 2015 Bokai Cao, Xiangnan Kong, Philip S. Yu

Brain disorder data poses many unique challenges for data mining research.

Multi-View Factorization Machines

1 code implementation3 Jun 2015 Bokai Cao, Hucheng Zhou, Guoqiang Li, Philip S. Yu

In this paper, we propose a general predictor, named multi-view machines (MVMs), that can effectively include all the possible interactions between features from multiple views.

Meta Path-Based Collective Classification in Heterogeneous Information Networks

no code implementations20 May 2013 Xiangnan Kong, Bokai Cao, Philip S. Yu, Ying Ding, David J. Wild

Moreover, by considering different linkage paths in the network, one can capture the subtlety of different types of dependencies among objects.

Classification General Classification

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