Liang Yang 杨亮

"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 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).

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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