activity
20192021
most citedGraph Inference Learning for Semi-supervised Classification

18 citations · 46 across the 7 of their papers we have counts for

collaborators

8 papers

cs.NI20213 cited

Going Deeper in Frequency Convolutional Neural Network: A Theoretical Perspective

Xiaohan Zhu, Zhen Cui, Tong Zhang +2

Convolutional neural network (CNN) is one of the most widely-used successful architectures in the era of deep learning. However, the high-computational cost of CNN still hampers mo…

cs.LG20213 cited

Spatial-Temporal Tensor Graph Convolutional Network for Traffic Prediction

Xuran Xu, Tong Zhang, Chunyan Xu +2

Accurate traffic prediction is crucial to the guidance and management of urban traffics. However, most of the existing traffic prediction models do not consider the computational b…

cs.IR2020

Interest-Behaviour Multiplicative Network for Resource-limited Recommendation

Qianliang Wu, Tong Zhang, Zhen Cui +1

Resource constraints, e.g. limited product inventory or financial strength, may affect consumers' choices or preferences in some recommendation tasks but are usually ignored in pre…

cs.CV20202 cited

Instance-Aware Graph Convolutional Network for Multi-Label Classification

Yun Wang, Tong Zhang, Zhen Cui +2

Graph convolutional neural network (GCN) has effectively boosted the multi-label image recognition task by introducing label dependencies based on statistical label co-occurrence o…

cs.LG2020

Graph Wasserstein Correlation Analysis for Movie Retrieval

Xueya Zhang, Tong Zhang, Xiaobin Hong +2

Movie graphs play an important role to bridge heterogenous modalities of videos and texts in human-centric retrieval. In this work, we propose Graph Wasserstein Correlation Analysi…

cs.LG202018 cited

Graph Inference Learning for Semi-supervised Classification

Chunyan Xu, Zhen Cui, Xiaobin Hong +3

In this work, we address semi-supervised classification of graph data, where the categories of those unlabeled nodes are inferred from labeled nodes as well as graph structures. Re…