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Liang Yang 0002
Person information
- affiliation: Hebei University of Technology, School of Computer Science and Engineering, Tianjin, China
- affiliation (former): Tianjin University of Commerce, School of Information Engineering, China
- affiliation (PhD 2016): Chinese Academy of Sciences, State Key Laboratory of Information Security, Beijing, China
Other persons with the same name
- Liang Yang (aka: Li'ang Yang) — disambiguation page
- Liang Yang 0001 — Hunan University, College of Computer Science and Electronic Engineering, Changsha, China (and 4 more)
- Liang Yang 0003 — Dalian University of Technology, Department of Computer Science and Technology, China
- Liang Yang 0004 — Zhejiang University, College of Animal Sciences, Hangzhou, China
- Liang Yang 0005 — Stanford University, CA, USA
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2020 – today
- 2024
- [j18]Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang:
Binary Graph Convolutional Network With Capacity Exploration. IEEE Trans. Pattern Anal. Mach. Intell. 46(5): 3031-3046 (2024) - [j17]Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang:
Heterophily-aware graph attention network. Pattern Recognit. 156: 110738 (2024) - [j16]Kun Sun, Tian-Fang Zhao, Xiaokun Wu, Liang Yang, Di Jin, Wei-Neng Chen:
Mining Multiplatform Opinions During Public Health Crisis: A Comparative Study. IEEE Trans. Comput. Soc. Syst. 11(2): 2121-2134 (2024) - [j15]Ming Gu, Tian-Fang Zhao, Liang Yang, Xiaokun Wu, Wei-Neng Chen:
Modeling Information Cocoons in Networked Populations: Insights From Backgrounds and Preferences. IEEE Trans. Comput. Soc. Syst. 11(3): 4497-4510 (2024) - [j14]Jiarui Yang, Chuan Wang, Liang Yang, Yuchen Jiang, Angelina Cao:
Adaptive Feature Learning for Unbiased Scene Graph Generation. IEEE Trans. Image Process. 33: 2252-2265 (2024) - [j13]Dongxiao He, Chundong Liang, Cuiying Huo, Zhiyong Feng, Di Jin, Liang Yang, Weixiong Zhang:
Analyzing Heterogeneous Networks With Missing Attributes by Unsupervised Contrastive Learning. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4438-4450 (2024) - [c41]Jiaming Zhuo, Feiyang Qin, Can Cui, Kun Fu, Bingxin Niu, Mengzhu Wang, Yuanfang Guo, Chuan Wang, Zhen Wang, Xiaochun Cao, Liang Yang:
Improving Graph Contrastive Learning via Adaptive Positive Sampling. CVPR 2024: 23179-23187 - [c40]Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang:
Understanding Heterophily for Graph Neural Networks. ICML 2024 - [c39]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 2024: 582-593 - [c38]Jiaming Zhuo, Can Cui, Kun Fu, Bingxin Niu, Dongxiao He, Chuan Wang, Yuanfang Guo, Zhen Wang, Xiaochun Cao, Liang Yang:
Graph Contrastive Learning Reimagined: Exploring Universality. WWW 2024: 641-651 - [i6]Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang:
Understanding Heterophily for Graph Neural Networks. CoRR abs/2401.09125 (2024) - 2023
- [j12]Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang:
Enabling Homogeneous GNNs to Handle Heterogeneous Graphs via Relation Embedding. IEEE Trans. Big Data 9(6): 1697-1710 (2023) - [j11]Dongxiao He, Tao Wang, Lu Zhai, Di Jin, Liang Yang, Yuxiao Huang, Zhiyong Feng, Philip S. Yu:
Adversarial Representation Mechanism Learning for Network Embedding. IEEE Trans. Knowl. Data Eng. 35(2): 1200-1213 (2023) - [c37]Lingfeng Tan, Yunhong Wang, Junfu Wang, Liang Yang, Xunxun Chen, Yuanfang Guo:
Deepfake Video Detection via Facial Action Dependencies Estimation. AAAI 2023: 5276-5284 - [c36]Liang Yang, Jiayi Wang, Dongxiao He, Chuan Wang, Xiaochun Cao, Bingxin Niu, Zhen Wang:
Graph Reciprocal Neural Networks by Abstracting Node as Attribute. ICDM 2023: 1463-1468 - [c35]Yuhan Chen, Yihong Luo, Jing Tang, Liang Yang, Siya Qiu, Chuan Wang, Xiaochun Cao:
LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity. IJCAI 2023: 3550-3558 - [c34]Jiaming Zhuo, Can Cui, Kun Fu, Bingxin Niu, Dongxiao He, Yuanfang Guo, Zhen Wang, Chuan Wang, Xiaochun Cao, Liang Yang:
Propagation is All You Need: A New Framework for Representation Learning and Classifier Training on Graphs. ACM Multimedia 2023: 481-489 - [c33]Liang Yang, Jiayi Wang, Tingting Zhang, Dongxiao He, Chuan Wang, Yuanfang Guo, Xiaochun Cao, Bingxin Niu, Zhen Wang:
Long Short-Term Graph Memory Against Class-imbalanced Over-smoothing. ACM Multimedia 2023: 2955-2963 - [c32]Jiarui Yang, Chuan Wang, Zeming Liu, Jiahong Wu, Dongsheng Wang, Liang Yang, Xiaochun Cao:
Focusing on Flexible Masks: A Novel Framework for Panoptic Scene Graph Generation with Relation Constraints. ACM Multimedia 2023: 4209-4218 - [c31]Liang Yang, Runjie Shi, Qiuliang Zhang, Bingxin Niu, Zhen Wang, Xiaochun Cao, Chuan Wang:
Self-supervised Graph Neural Networks via Low-Rank Decomposition. NeurIPS 2023 - [c30]Liang Yang, Qiuliang Zhang, Runjie Shi, Wenmiao Zhou, Bingxin Niu, Chuan Wang, Xiaochun Cao, Dongxiao He, Zhen Wang, Yuanfang Guo:
Graph Neural Networks without Propagation. WWW 2023: 469-477 - [i5]Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang:
Heterophily-Aware Graph Attention Network. CoRR abs/2302.03228 (2023) - [i4]Yuhan Chen, Yihong Luo, Jing Tang, Liang Yang, Siya Qiu, Chuan Wang, Xiaochun Cao:
LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity. CoRR abs/2305.04225 (2023) - 2022
- [j10]Liang Yang, Yuanfang Guo, Junhua Gu, Di Jin, Bo Yang, Xiaochun Cao:
Probabilistic Graph Convolutional Network via Topology-Constrained Latent Space Model. IEEE Trans. Cybern. 52(4): 2123-2136 (2022) - [c29]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 2022: 4327-4336 - [c28]Liang Yang, Weihang Peng, Wenmiao Zhou, Bingxin Niu, Junhua Gu, Chuan Wang, Yuanfang Guo, Dongxiao He, Xiaochun Cao:
Difference Residual Graph Neural Networks. ACM Multimedia 2022: 3356-3364 - [c27]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 2022 - [c26]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 2022: 1127-1135 - [i3]Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang:
Relation Embedding based Graph Neural Networks for Handling Heterogeneous Graph. CoRR abs/2209.11414 (2022) - [i2]Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang:
Binary Graph Convolutional Network with Capacity Exploration. CoRR abs/2210.13149 (2022) - 2021
- [j9]Ming Gu, Tianfang Zhao, Wei Liu, Xiaokun Wu, Liang Yang:
Toward Identifying Key Gene Group in the Occurrence and Development of Lung Adenocarcinoma. IEEE Access 9: 26156-26167 (2021) - [j8]Liang Yang, Weixun Li, Yuanfang Guo, Junhua Gu:
Graph-CAT: Graph Co-Attention Networks via local and global attribute augmentations. Future Gener. Comput. Syst. 118: 170-179 (2021) - [c25]Liang Yang, Chuan Wang, Junhua Gu, Xiaochun Cao, Bingxin Niu:
Why Do Attributes Propagate in Graph Convolutional Neural Networks? AAAI 2021: 4590-4598 - [c24]Junfu Wang, Yunhong Wang, Zhen Yang, Liang Yang, Yuanfang Guo:
Bi-GCN: Binary Graph Convolutional Network. CVPR 2021: 1561-1570 - [c23]Liang Yang, Fan Wu, Zichen Zheng, Bingxin Niu, Junhua Gu, Chuan Wang, Xiaochun Cao, Yuanfang Guo:
Heterogeneous Graph Information Bottleneck. IJCAI 2021: 1638-1645 - [c22]Liang Yang, Mengzhe Li, Liyang Liu, Bingxin Niu, Chuan Wang, Xiaochun Cao, Yuanfang Guo:
Diverse Message Passing for Attribute with Heterophily. NeurIPS 2021: 4751-4763 - [c21]Di Jin, Cuiying Huo, Chundong Liang, Liang Yang:
Heterogeneous Graph Neural Network via Attribute Completion. WWW 2021: 391-400 - 2020
- [j7]Chuan Wang, Huazhu Fu, Liang Yang, Xiaochun Cao:
Text Co-Detection in Multi-View Scene. IEEE Trans. Image Process. 29: 4627-4642 (2020) - [c20]Liang Yang, Junhua Gu, Chuan Wang, Xiaochun Cao, Lu Zhai, Di Jin, Yuanfang Guo:
Toward Unsupervised Graph Neural Network: Interactive Clustering and Embedding via Optimal Transport. ICDM 2020: 1358-1363 - [c19]Liang Yang, Yuexue Wang, Junhua Gu, Chuan Wang, Xiaochun Cao, Yuanfang Guo:
JANE: Jointly Adversarial Network Embedding. IJCAI 2020: 1381-1387 - [c18]Dongxiao He, Lu Zhai, Zhigang Li, Di Jin, Liang Yang, Yuxiao Huang, Philip S. Yu:
Adversarial Mutual Information Learning for Network Embedding. IJCAI 2020: 3321-3327 - [c17]Tianfang Zhao, Wei-Neng Chen, Xiaokun Wu, Liang Yang, Qiang Yang:
Discrete Resource Allocation in Epidemic Control with Heuristic Majority-Voting Particle Swarm Optimization. SMC 2020: 2058-2065 - [c16]Liang Yang, Fan Wu, Junhua Gu, Chuan Wang, Xiaochun Cao, Di Jin, Yuanfang Guo:
Graph Attention Topic Modeling Network. WWW 2020: 144-154 - [i1]Junfu Wang, Yunhong Wang, Zhen Yang, Liang Yang, Yuanfang Guo:
Bi-GCN: Binary Graph Convolutional Network. CoRR abs/2010.07565 (2020)
2010 – 2019
- 2019
- [c15]Jing Wang, Atsushi Suzuki, Linchuan Xu, Feng Tian, Liang Yang, Kenji Yamanishi:
Orderly Subspace Clustering. AAAI 2019: 5264-5272 - [c14]Di Jin, Zhigang Li, Liang Yang, Dongxiao He, Pengfei Jiao, Lu Zhai:
Adversarial Capsule Learning for Network Embedding. ICTAI 2019: 214-221 - [c13]Liang Yang, Zesheng Kang, Xiaochun Cao, Di Jin, Bo Yang, Yuanfang Guo:
Topology Optimization based Graph Convolutional Network. IJCAI 2019: 4054-4061 - [c12]Liang Yang, Zhiyang Chen, Junhua Gu, Yuanfang Guo:
Dual Self-Paced Graph Convolutional Network: Towards Reducing Attribute Distortions Induced by Topology. IJCAI 2019: 4062-4069 - [c11]Liang Yang, Fan Wu, Yingkui Wang, Junhua Gu, Yuanfang Guo:
Masked Graph Convolutional Network. IJCAI 2019: 4070-4077 - [c10]Di Jin, Jiantao Huang, Pengfei Jiao, Liang Yang, Dongxiao He, Françoise Fogelman-Soulié, Yuxiao Huang:
A Novel Generative Topic Embedding Model by Introducing Network Communities. WWW 2019: 2886-2892 - 2018
- [j6]Jinxin Cao, Di Jin, Liang Yang, Jianwu Dang:
Incorporating network structure with node contents for community detection on large networks using deep learning. Neurocomputing 297: 71-81 (2018) - [j5]Zhiyong Chen, Si Liu, Yanlong Zhai, Jia Lin, Xiaochun Cao, Liang Yang:
Human parsing by weak structural label. Multim. Tools Appl. 77(15): 19795-19809 (2018) - [c9]Liang Yang, Yuanfang Guo, Xiaochun Cao:
Multi-Facet Network Embedding: Beyond the General Solution of Detection and Representation. AAAI 2018: 499-506 - [c8]Di Jin, Meng Ge, Liang Yang, Dongxiao He, Longbiao Wang, Weixiong Zhang:
Integrative Network Embedding via Deep Joint Reconstruction. IJCAI 2018: 3407-3413 - [c7]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 2018: 3613-3619 - 2017
- [j4]Chuan Wang, Hua Zhang, Liang Yang, Xiaochun Cao, Hongkai Xiong:
Multiple Semantic Matching on Augmented N-Partite Graph for Object Co-Segmentation. IEEE Trans. Image Process. 26(12): 5825-5839 (2017) - [c6]Jing Wang, Feng Tian, Xiao Wang, Hongchuan Yu, Chang Hong Liu, Liang Yang:
Multi-Component Nonnegative Matrix Factorization. IJCAI 2017: 2922-2928 - 2016
- [j3]Xiaojing Yao, Ling Peng, Liang Yang, Tianhe Chi:
A fast space-saving algorithm for maximal co-location pattern mining. Expert Syst. Appl. 63: 310-323 (2016) - [j2]Xiaochun Cao, Liang Yang, Xiaojie Guo:
Total Variation Regularized RPCA for Irregularly Moving Object Detection Under Dynamic Background. IEEE Trans. Cybern. 46(4): 1014-1027 (2016) - [c5]Xiao Wang, Di Jin, Xiaochun Cao, Liang Yang, Weixiong Zhang:
Semantic Community Identification in Large Attribute Networks. AAAI 2016: 265-271 - [c4]Liang Yang, Xiaochun Cao, Dongxiao He, Chuan Wang, Xiao Wang, Weixiong Zhang:
Modularity Based Community Detection with Deep Learning. IJCAI 2016: 2252-2258 - 2015
- [j1]Liang Yang, Xiaochun Cao, Di Jin, Xiao Wang, Dan Meng:
A Unified Semi-Supervised Community Detection Framework Using Latent Space Graph Regularization. IEEE Trans. Cybern. 45(11): 2585-2598 (2015) - [c3]Menghao Li, Liang Yang, Zimu Yuan, Rui Zhang, Rui Xue:
An Approach for Mitigating Potential Threats in Practical SSO Systems. Inscrypt 2015: 209-226 - [c2]Chuan Wang, Hua Zhang, Liang Yang, Si Liu, Xiaochun Cao:
Deep People Counting in Extremely Dense Crowds. ACM Multimedia 2015: 1299-1302 - 2014
- [c1]Xiaojie Guo, Xinggang Wang, Liang Yang, Xiaochun Cao, Yi Ma:
Robust Foreground Detection Using Smoothness and Arbitrariness Constraints. ECCV (7) 2014: 535-550
Coauthor Index
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