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Latent Structures Mining with Contrastive Modality Fusion for Multimedia Recommendation


Nov 01, 2021
Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Mengqi Zhang, Shu Wu, Liang Wang

* 12 pages; in submission to IEEE TKDE. arXiv admin note: substantial text overlap with arXiv:2104.09036 

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An Empirical Study of Graph Contrastive Learning


Sep 02, 2021
Yanqiao Zhu, Yichen Xu, Qiang Liu, Shu Wu

* Work in progress. Open-sourced library at https://github.com/GraphCL/PyGCL 

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Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning


Aug 31, 2021
Yanqiao Zhu, Yichen Xu, Hejie Cui, Carl Yang, Qiang Liu, Shu Wu

* KDD Workshop on Deep Learning on Graphs: Method and Applications ([email protected] 2021) 

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Deep Contrastive Learning for Multi-View Network Embedding


Aug 16, 2021
Mengqi Zhang, Yanqiao Zhu, Shu Wu, Liang Wang

* Work in progress 

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Deep Active Learning for Text Classification with Diverse Interpretations


Aug 15, 2021
Qiang Liu, Yanqiao Zhu, Zhaocheng Liu, Yufeng Zhang, Shu Wu

* Accepted to CIKM 2021. Authors' version 

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BrainNNExplainer: An Interpretable Graph Neural Network Framework for Brain Network based Disease Analysis


Jul 11, 2021
Hejie Cui, Wei Dai, Yanqiao Zhu, Xiaoxiao Li, Lifang He, Carl Yang

* This paper has been accepted to ICML 2021 Workshop on Interpretable Machine Learning in Healthcare 

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Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis


Jul 07, 2021
Yanqiao Zhu, Hejie Cui, Lifang He, Lichao Sun, Carl Yang

* Accepted to ICML 2021 Workshop on Computational Approaches to Mental Health 

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Graph Symbiosis Learning


Jun 10, 2021
Liang Zeng, Jin Xu, Zijun Yao, Yanqiao Zhu, Jian Li


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Mining Latent Structures for Multimedia Recommendation


Apr 19, 2021
Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Shuhui Wang, Liang Wang

* Work in progress, 10 pages 

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Deep Graph Structure Learning for Robust Representations: A Survey


Mar 04, 2021
Yanqiao Zhu, Weizhi Xu, Jinghao Zhang, Qiang Liu, Shu Wu, Liang Wang

* 8 pages, in submission to IJCAI 2021 (Survey Track) 

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Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction


Jan 11, 2021
Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang

* 11 pages, work in progress 

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Deep Active Graph Representation Learning


Oct 30, 2020
Yanqiao Zhu, Weizhi Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang

* Preliminary work, 10 pages 

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Graph Contrastive Learning with Adaptive Augmentation


Oct 27, 2020
Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang

* Work in progress; 11 pages, 3 figures, 5 tables. arXiv admin note: substantial text overlap with arXiv:2006.04131 

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CAGNN: Cluster-Aware Graph Neural Networks for Unsupervised Graph Representation Learning


Sep 03, 2020
Yanqiao Zhu, Yichen Xu, Feng Yu, Shu Wu, Liang Wang

* 21 pages, in submission to ACM TIST 

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Deep Graph Contrastive Representation Learning


Jun 07, 2020
Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang

* Work in progress, 17 pages 

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TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation


May 06, 2020
Feng Yu, Yanqiao Zhu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan

* 5 pages, accepted to SIGIR 2020, authors' version 

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GraphAIR: Graph Representation Learning with Neighborhood Aggregation and Interaction


Nov 14, 2019
Fenyu Hu, Yanqiao Zhu, Shu Wu, Weiran Huang, Liang Wang, Tieniu Tan

* 8 pages, in submission to IEEE Transactions on Knowledge and Data Engineering 

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Semi-supervised Node Classification via Hierarchical Graph Convolutional Networks


Mar 05, 2019
Fenyu Hu, Yanqiao Zhu, Shu Wu, Liang Wang, Tieniu Tan

* 7 pages, 3 figures 

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Session-based Recommendation with Graph Neural Networks


Nov 05, 2018
Shu Wu, Yuyuan Tang, Yanqiao Zhu, Liang Wang, Xing Xie, Tieniu Tan

* 9 pages, 4 figures, accepted by AAAI Conference on Artificial Intelligence (AAAI-19) 

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Active Learning for Wireless IoT Intrusion Detection


Aug 04, 2018
Kai Yang, Jie Ren, Yanqiao Zhu, Weiyi Zhang

* 7 pages, 4 figures, accepted by IEEE Wireless Communications 

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