70 citations · 91 across the 6 of their papers we have counts for
7 papers
Learning Inter-Modal Correspondence and Phenotypes from Multi-Modal Electronic Health Records
Kejing Yin, William K. Cheung, Benjamin C. M. Fung +1
Non-negative tensor factorization has been shown a practical solution to automatically discover phenotypes from the electronic health records (EHR) with minimal human supervision.…
A Structural Representation Learning for Multi-relational Networks
Xin Li, Huiting Hong, Lin Liu +1
Most of the existing multi-relational network embedding methods, e.g., TransE, are formulated to preserve pair-wise connectivity structures in the networks. With the observations t…
Personalized Next Point-of-Interest Recommendation via Latent Behavior Patterns Inference
Jing He, Xin Li, Lejian Liao +1
In this paper, we address the problem of personalized next Point-of-interest (POI) recommendation which has become an important and very challenging task for location-based social…
Towards well-specified semi-supervised model-based classifiers via structural adaptation
Zhaocai Sun, William K. Cheung, Xiaofeng Zhang +1
Semi-supervised learning plays an important role in large-scale machine learning. Properly using additional unlabeled data (largely available nowadays) often can improve the machin…
Learning Stylometric Representations for Authorship Analysis
Steven H. H. Ding, Benjamin C. M. Fung, Farkhund Iqbal +1
Authorship analysis (AA) is the study of unveiling the hidden properties of authors from a body of exponentially exploding textual data. It extracts an author's identity and sociol…
Higher-Order Markov Tag-Topic Models for Tagged Documents and Images
Jia Zeng, Wei Feng, William K. Cheung +1
This paper studies the topic modeling problem of tagged documents and images. Higher-order relations among tagged documents and images are major and ubiquitous characteristics, and…
Learning Topic Models by Belief Propagation
Jia Zeng, William K. Cheung, Jiming Liu
Latent Dirichlet allocation (LDA) is an important hierarchical Bayesian model for probabilistic topic modeling, which attracts worldwide interests and touches on many important app…