45 citations · 153 across the 14 of their papers we have counts for
5 papers · 1 filter
Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment
Dinghan Shen, Xinyuan Zhang, Ricardo Henao +1
Network embeddings, which learn low-dimensional representations for each vertex in a large-scale network, have received considerable attention in recent years. For a wide range of…
Joint Embedding of Words and Labels for Text Classification
Guoyin Wang, Chunyuan Li, Wenlin Wang +5
Word embeddings are effective intermediate representations for capturing semantic regularities between words, when learning the representations of text sequences. We propose to vie…
Diffusion Maps for Textual Network Embedding
Xinyuan Zhang, Yitong Li, Dinghan Shen +1
Textual network embedding leverages rich text information associated with the network to learn low-dimensional vectorial representations of vertices. Rather than using typical natu…
Nonlocal Low-Rank Tensor Factor Analysis for Image Restoration
Xinyuan Zhang, Xin Yuan, Lawrence Carin
Low-rank signal modeling has been widely leveraged to capture non-local correlation in image processing applications. We propose a new method that employs low-rank tensor factor an…
Multi-Label Learning from Medical Plain Text with Convolutional Residual Models
Xinyuan Zhang, Ricardo Henao, Zhe Gan +2
Predicting diagnoses from Electronic Health Records (EHRs) is an important medical application of multi-label learning. We propose a convolutional residual model for multi-label cl…