4.8k citations · 5.9k across the 13 of their papers we have counts for
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Learning Hierarchical Representations of Electronic Health Records for Clinical Outcome Prediction
Luchen Liu, Haoran Li, Zhiting Hu +4
Clinical outcome prediction based on the Electronic Health Record (EHR) plays a crucial role in improving the quality of healthcare. Conventional deep sequential models fail to cap…
Less is More: Learning Prominent and Diverse Topics for Data Summarization
Jian Tang, Cheng Li, Ming Zhang +1
Statistical topic models efficiently facilitate the exploration of large-scale data sets. Many models have been developed and broadly used to summarize the semantic structure in ne…
Visualizing Large-scale and High-dimensional Data
Jian Tang, Jingzhou Liu, Ming Zhang +1
We study the problem of visualizing large-scale and high-dimensional data in a low-dimensional (typically 2D or 3D) space. Much success has been reported recently by techniques tha…
LINE: Large-scale Information Network Embedding
Jian Tang, Meng Qu, Mingzhe Wang +3
This paper studies the problem of embedding very large information networks into low-dimensional vector spaces, which is useful in many tasks such as visualization, node classifica…
"Look Ma, No Hands!" A Parameter-Free Topic Model
Jian Tang, Ming Zhang, Qiaozhu Mei
It has always been a burden to the users of statistical topic models to predetermine the right number of topics, which is a key parameter of most topic models. Conventionally, auto…