3 citations · 4 across the 2 of their papers we have counts for
5 papers
Long-tailed Extreme Multi-label Text Classification with Generated Pseudo Label Descriptions
Ruohong Zhang, Yau-Shian Wang, Yiming Yang +3
Extreme Multi-label Text Classification (XMTC) has been a tough challenge in machine learning research and applications due to the sheer sizes of the label spaces and the severe da…
Exploiting Local and Global Features in Transformer-based Extreme Multi-label Text Classification
Ruohong Zhang, Yau-Shian Wang, Yiming Yang +2
Extreme multi-label text classification (XMTC) is the task of tagging each document with the relevant labels from a very large space of predefined categories. Recently, large pre-t…
Knowledge Embedding Based Graph Convolutional Network
Donghan Yu, Yiming Yang, Ruohong Zhang +1
Recently, a considerable literature has grown up around the theme of Graph Convolutional Network (GCN). How to effectively leverage the rich structural information in complex graph…
Correlation-aware Unsupervised Change-point Detection via Graph Neural Networks
Ruohong Zhang, Yu Hao, Donghan Yu +3
Change-point detection (CPD) aims to detect abrupt changes over time series data. Intuitively, effective CPD over multivariate time series should require explicit modeling of the d…
Graph-Revised Convolutional Network
Donghan Yu, Ruohong Zhang, Zhengbao Jiang +2
Graph Convolutional Networks (GCNs) have received increasing attention in the machine learning community for effectively leveraging both the content features of nodes and the linka…