Liang Yang 杨亮


Ph.D & Professor

I received my Ph.D degree from the State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences in 2016. My advisor was Prof. Xiaochun Cao. I am a professor in School of Artificial Intelligence, Hebei University of Technology. My current research interests include community detection, machine learning and computer vision.

Experience

2021 - now

Professor @ Hebei University of Technology

2018 - 2021

Associate Professor @ Hebei University of Technology

2010 - 2018

Assistant Professor @ Tianjin University of Commerce

2009 - 2010

R&D Engineer @ Baidu

2007 - 2009

R&D Engineer @ Tencent

Education

2013 - 2016

Institute of Information Engineering, CAS

2004 - 2007

Nankai Univiersity (Computational Mathematics)

2000 - 2004

Nankai Univiersity (Computational Mathematics)

Foundations

"Research on Modeling and Representation Learning for Graph Data in Complex Scenarios". National Natural Science Foundation of China (NSFC) (62376088), 2024-2027.

"The Research on Large-scale Network Partition by Incorporating Heterogeneous Topology and Semantic Information". National Natural Science Foundation of China (NSFC) (61972442), 2020-2023.

"Research on Overlapping Community Detection and Model Selection with Actively Selected Heterogeneous Supervised Information". National Natural Science Foundation of China (NSFC) (61503281), 2016-2018.

"Research and Application of General Artificial Intelligence Based on Graph Machine Learning". Natural Science Foundation of Hebei Province (F2024202047).

"Research on the Representation Learning in Large-scale Multimodal Cyberspace Based on the Bayesian Graph Neural Networks". Natural Science Foundation of Hebei Province (F2020202040).

"The Research on Large Scale Cyberspace Intelligence Analysis Based Multi-modal Representation Learning". Natural Science Foundation of Tianjin (20JCYBJC00650).

"Vehicle-Road Cooperative Perception System Based on Multi-source Information Fusion". Key Research and Development Project of Hebei Province (20350802D).

Publications  [Google Scholar]   [DBLP]

Jiaming Zhuo, Yintong Lu, Hui Ning, Kun Fu, Bingxin Niu, Dongxiao He, Chuan Wang, Yuanfang Guo, Zhen Wang, Xiaochun Cao, Liang Yang* (Corresponding Author). "Unified Graph Augmentations for Generalized Contrastive Learning on Graphs". NeurIPS-24

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Jiaming Zhuo, Feiyang Qin, Can Cui, Kun Fu, Bingxin Niu, Mengzhu Wang, Yuanfang Guo, Chuan Wang, Zhen Wang, Xiaochun Cao, Liang Yang* (Corresponding Author). "Improving Graph Contrastive Learning via Adaptive Positive Sampling". CVPR-24

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Liang Yang, Weixiao Hu, Jizhong Xu, Runjie Shi, Dongxiao He, Chuan Wang, Xiaochun Cao, Zhen Wang, Bingxin Niu, Yuanfang Guo. "GAUSS: GrAph-customized Universal Self-Supervised Learning". WWW-24

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Jiaming Zhuo, Can Cui, Kun Fu, Bingxin Niu, Dongxiao He, Chuan Wang, Yuanfang Guo, Zhen Wang, Xiaochun Cao, Liang Yang* (Corresponding Author). "Graph Contrastive Learning Reimagined: Exploring Universality". WWW-24

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Liang Yang, Runjie Shi, Qiuliang Zhang, Bingxin Niu, Zhen Wang, Chuan Wang, Xiaochun Cao. "Self-supervised Graph Neural Networks via Low-Rank Decomposition". NeurIPS-23

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Liang Yang, Jiayi Wang, Dongxiao He, Chuan Wang, Xiaochun Cao, Bingxin Niu and Zhen Wang. "Graph Reciprocal Neural Networks by Abstracting Node as Attribute". ICDM-23

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Jiaming Zhuo, Can Cui, Dongxiao He, Yuanfang Guo, Zhen Wang, Chuan Wang, Xiaochun Cao, and Liang Yang* (Corresponding Author). "Propagation is All You Need: A New Framework for Representation Learning and Classifier Training on Graphs". ACMMM-23 (Oral)

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Liang Yang, Jiayi Wang, Tingting Zhang, Dongxiao He, Chuan Wang, Yuanfang Guo, Xiaochun Cao, Bingxin Niu and Zhen Wang. "Long Short-Term Graph Memory Against Class-imbalanced Over-smoothing". ACMMM-23

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Liang Yang, Qiuliang Zhang, Runjie Shi, Wenmiao Zhou, Bingxin Niu, Chuan Wang, Xiaochun Cao, Dongxiao He, Yuanfang Guo and Zhen Wang. "Graph Neural Network without Propagation". WWW-23

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Liang Yang, Lina Kang, Qiuliang Zhang, Mengzhe Li, Bingxin Niu, Dongxiao He, Zhen Wang, Chuan Wang, Xiaochun Cao, Yuanfang Guo. "OPEN: Orthogonal Propagation with Ego-Network Modeling". NeurIPS-22

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Liang Yang, Weihang Peng, Wenmiao Zhou, Bingxin Niu, Junhua Gu, Chuan Wang, Yuanfang Guo, Dongxiao He, and Xiaochun Cao. "Difference Residual Graph Neural Networks". ACMMM-22

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Dongxiao He, Chundong Liang, Cuiying Huo, Zhiyong Feng, Di Jin, Liang Yang* (Corresponding Author), and Weixiong Zhang. "Analyzing Heterogeneous Networks with Missing Attributes by Unsupervised Contrastive Learning". IEEE Transactions on Neural Networks and Learning Systems

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Liang Yang, Wenmiao Zhou, Weihang Peng, Bingxin Niu, Junhua Gu, Chuan Wang, Xiaochun Cao, Dongxiao He. "Graph Neural Networks Beyond Compromise Between Attribute and Topology". WWW-22

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Liang Yang, Cheng Chen, Weixun Li, Bingxin Niu, Junhua Gu, Chuan Wang, Dongxiao He, Yuanfang Guo, Xiaochun Cao. "Self-supervised Graph Neural Networks via Diverse and Interactive Message Passing". AAAI-22

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Liang Yang, Mengzhe Li, Liyang Liu, Bingxin Niu, Chuan Wang, Xiaochun Cao, Yuanfang Guo. "Diverse Message Passing for Attribute with Heterophily". NeurIPS-21

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Di Jin, Cuiying Huo, Chundong Liang, and Liang Yang* (Corresponding Author). "Heterogeneous Graph Neural Network via Attribute Completion". WWW-21 (Best Paper Runner-up)

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Liang Yang, Fan Wu, Zichen Zheng, Bingxin Niu, Junhua Gu, Chuan Wang, Xiaochun Cao and Yuanfang Guo. "Heterogeneous Graph Information Bottleneck". IJCAI-21

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Liang Yang, Weixun Li, Yuanfang Guo, and Junhua Gu. "Graph-CAT: Graph Co-Attention Networks via local and global attribute augmentations". Future Generation Computer Systems. 118: 170-179 (2021)

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Liang Yang, Chuan Wang, Xiaochun Cao, Bingxin Niu, and Junhua Gu. "Why Do Attributes Propagate in Graph Convolutional Neural Networks?". AAAI-21

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Liang Yang, Yuangfang Guo, Xiaochun Cao, Chuan Wang, Lu Zhai, Di Jin, and Junhua Gu. "Toward Unsupervised Graph Neural Network: Interactive Clustering and Embedding via Optimal Transport". ICDM-20

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Liang Yang, Yuanfang Guo, Junhua Gu, Di Jin, Bo Yang, Xiaochun Cao. "Probabilistic Graph Convolutional Network via Topology-Constrained Latent Space Model". IEEE Trans. on Cybernetics

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Liang Yang, Yuanfang Guo, Xiaochun Cao, Junhua Gu, Di Jin, Fan Wu and Chuan Wang. "Graph Attention Topic Modeling Network". The Web Conference (WWW) 2020. Full paper (Oral)

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Liang Yang, Yuexue Wang, Junhua Gu, Chuan Wang, Xiaochun Cao, Yuanfang Guo. "JANE: Jointly Adversarial Network Embedding". IJCAI-20.

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Liang Yang, Yuexue Wang, Junhua Gu, Xiaochun Cao, Xiao Wang, Di Jin, Guiguang Ding, Jungong Han and Weixiong Zhang. "Autonomous Semantic Community Detection via Adaptively Weighted Low-rank Approximation". ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 2019, 15(3s): 98.

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Liang Yang, Zhiyang Chen, Junhua Gu and Yuanfang Guo. "Dual Self-Paced Graph Convolutional Network: Towards Reducing Attribute Distortions Induced by Topology". IJCAI-19.

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Liang Yang, Fan Wu, Yingkui Wang, Junhua Gu and Yuanfang Guo. "Masked Graph Convolutional Network". IJCAI-19.

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Liang Yang, Zesheng Kang, Xiaochun Cao, Di Jin, Bo Yang and Yuanfang Guo. "Topology Optimization based Graph Convolutional Network". IJCAI-19.

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Liang Yang, Yuanfang Guo, Di Jin, Huazhu Fu, Xiaochun Cao. "3-in-1 Correlated Embedding via Adaptive Exploration of the Structure and Semantic Subspaces.". IJCAI-18.

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Liang Yang, Yuanfang Guo and Xiaochun Cao. "Multi-facet Network Embedding: Beyond the General Solution of Detection and Representation". AAAI-18.

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Liang Yang, Di Jin, Dongxiao He, Huazhu Fu, Xiaochun Cao and Francoise Fogelman-Soulie. "Improving the Efficiency and Effectiveness of Community Detection via Prior-Induced Equivalent Super-Network". Scientific Reports, 2017, 7, 634.

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Liang Yang, Meng Ge, Di Jin, Dongxiao He, Huazhu Fu, Jing Wang and Xiaochun Cao. "Exploring the roles of cannot-link constraint in community detection via Multi-variance Mixed Gaussian Generative Model". PLOS ONE, 2017, 12(7): e0178029.

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Liang Yang, Xiaochun Cao, Dongxiao He, Chuan Wang, Xiao Wang and Weixiong Zhang. "Modularity based Community Detection with Deep Learning". IJCAI-16: 2252-2258 (Oral).

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Liang Yang, Di Jin, Xiao Wang and Xiaochun Cao. "Active Link Selection for Efficient Semi-supervised Community Detection". Scientific Reports, 2015, 5, 9039.

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Liang Yang, Xiaochun Cao, Di Jin, Xiao Wang and Dan Meng. "A Unified Semi-Supervised Community Detection Framework Using Latent Space Graph Regularization". IEEE Trans. on Cybernetics, 2015, 45(11): 2585-2598.

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Xiaochun Cao, Liang Yang and Xiaojie Guo. "Total Variation Regularized RPCA for Irregularly Moving Object Detection under Dynamic Background". IEEE Trans. on Cybernetics, 2016, 46(4): 1014-1027.

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Dongxiao He, Lu Zhai, Zhigang Li, Liang Yang, Di Jin, Yuxiao Huang, Philip S. Yu. "Adversarial Mutual Information Learning for Network Embedding". IJCAI-20.

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Junfu Wang, Yunhong Wang, Zhen Yang, Liang Yang, Yuanfang Guo. "Bi-GCN: Binary Graph Convolutional Network". CVPR-21 (Oral)

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Di Jin, Meng Ge, Liang Yang*, Longbiao Wang, Dongxiao He and Weixiong Zhang. "Integrative Network Embedding via Deep Joint Reconstruction". IJCAI-18.

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Di Jin, Jiantao Huang, Pengfei Jiao, Liang Yang*, Dongxiao He, Franoise Soulie-Fogelman and Yuxiao Huang. "A Novel Generative Topic Embedding Model by Introducing Network Communities". WWW-19.

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Jinxin Cao, Di Jin, Liang Yang and Jianwu Dang. "Incorporating network structure with node contents for Community Detection on large networks using deep learning". Neurocomputing, 2018, 297: 71-81.

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Menghao Li, Liang Yang, Zimu Yuan, Rui Zhang and Rui Xue. "An Approach for Mitigating Potential Threats in Practical SSO Systems". Inscrypt 2015.

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Chuan Wang, Huazhu Fu, Liang Yang, Xiaochun Cao. "Text Co-Detection in Multi-View Scene". IEEE Trans. on Image Processing, 2020, 29(12): 4627-4642.

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Chuan Wang, Hua Zhang, Liang Yang, Xiaochun Cao and Hongkai Xiong. "Multiple Semantic Matching on Augmented N -Partite Graph for Object Co-Segmentation". IEEE Trans. on Image Processing, 2017, 26(12): 5825-5839.

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Xiaojie Guo, Xinggang Wang, Liang Yang, Xiaochun Cao and Yi Ma. "Robust Foreground Detection Using Smoothness and Arbitrariness Constraints". ECCV-14.

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Chuan Wang, Hua Zhang, Liang Yang, Si Liu, and Xiaochun Cao. "Deep People Counting in Extremely Dense Crowds". ACM MM-15.

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Xiao Wang, Di Jin, Xiaochun Cao, Liang Yang and Weixiong Zhang. "Semantic community identification in large attribute networks". AAAI-16.

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Xiaojing Yao, Ling Peng, Liang Yang and Tianhe Chi. "A fast space-saving algorithm for maximal co-location pattern mining". Expert Systems with Applications, 2016, 63: 310-323.

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Jing Wang, Feng Tian, Xiao Wang, Hongchuan Yu, Chang Hong Liu and Liang Yang. "Multi-Component Nonnegative Matrix Factorization". IJCAI-17: 2922-2928..

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Zhiyong Chen, Si Liu, Yanlong Zhai, Jia Lin, Xiaochun Cao and Liang Yang. "Human parsing by weak structural label". Multimedia Tools and Applications, 2017.

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Xiaojing Yao, Liujia Chen, Congcong Wen, Ling Peng, Liang Yang, Tianhe Chi, Xiaomeng Wang and Wenhao Y. "A spatial co-location mining algorithm that includes adaptive proximity improvements and distant instance references". International Journal of Geographical Information Science, 2018, 32(5): 980-1005.

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Jing Wang, Atsushi Suzuki, Linchuan Xu, Feng Tian, Liang Yang, Kenji Yamanishi. "Orderly Subspace Clustering". AAAI-19.

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Contact

Address
State Key Laboratory of Information Security,
Institute of Information Engineering,
89A, Minzhuang Rd. Haidian District,
Beijing 100093, China
Email
yangliang@vip.qq.com
Phone
(86) 137-5249-7682
Weibo