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2020 – today
- 2024
[j14]Chen Hou
, Cangqi Zhou, Chu-Ge Wu, Rui Cong, Kun Li:
Optimization of Cloud-Based Multi-Agent System for Trade-Off Between Trustworthiness of Data and Cost of Data Usage. IEEE Trans Autom. Sci. Eng. 21(1): 106-122 (2024)- [j13]Chen Hou, Cangqi Zhou, Qilong Huang, Chao-Bo Yan:
Cache Control of Edge Computing System for Tradeoff Between Delays and Cache Storage Costs. IEEE Trans Autom. Sci. Eng. 21(1): 827-843 (2024) - [j12]Cangqi Zhou, Hui Chen, Jing Zhang, Qianmu Li, Dianming Hu:
Quintuple-based Representation Learning for Bipartite Heterogeneous Networks. ACM Trans. Intell. Syst. Technol. 15(3): 61:1-61:19 (2024) - [j11]Jing Zhang, Ming Wu, Cangqi Zhou, Victor S. Sheng:
Active Crowdsourcing for Multilabel Annotation. IEEE Trans. Neural Networks Learn. Syst. 35(3): 3549-3559 (2024) - [j10]Hanrui Zhang, Qianmu Li, Shunmei Meng, Zhuoran Xu, Chaoxian Lv, Cangqi Zhou:
A safety fault diagnosis method on industrial intelligent control equipment. Wirel. Networks 30(5): 4287-4299 (2024) - [c18]Tong Lin, Cangqi Zhou, Qianmu Li, Dianming Hu:
Multi-level Disentangled Contrastive Learning on Heterogeneous Graphs. ICMLC 2024: 628-634 - [c17]Xiaoqian Jiang, Haiyang Diao, Cangqi Zhou, Jing Zhang:
Timeliness-Selective Incentive Federated Crowdsourcing. ICWS 2024: 632-642 - [i3]Jing Zhang, Xiaoqian Jiang, Yingjie Xie, Cangqi Zhou:
Heterogeneous Graph Contrastive Learning with Spectral Augmentation. CoRR abs/2407.00708 (2024) - 2023
- [j9]Qilong Huang, Li Yang, Qing-Shan Jia, Yaowen Qi, Cangqi Zhou, Xiaohong Guan:
A Simulation-Based Primal-Dual Approach for Constrained V2G Scheduling in a Microgrid of Building. IEEE Trans Autom. Sci. Eng. 20(3): 1851-1863 (2023) - [c16]Yingjie Xie, Qi Yan, Cangqi Zhou, Jing Zhang, Dianming Hu:
Heterogeneous Graph Contrastive Learning with Dual Aggregation Scheme and Adaptive Augmentation. APWeb/WAIM (4) 2023: 124-138 - [c15]Peishuo Liu, Cangqi Zhou, Xiao Liu, Jing Zhang, Qianmu Li:
Multi-Granularity Contrastive Learning for Graph with Hierarchical Pooling. ICANN (4) 2023: 499-511 - [c14]Peishuo Liu, Cangqi Zhou, Jing Zhang, Qianmu Li, Dianming Hu:
Hierarchical Graph Contrastive Learning via Debiasing Noise Samples with Adaptive Repelling Ratio. ICDM 2023: 418-427 - [i2]Xiang Li, Jing Zhang, Yali Yuan, Cangqi Zhou:
Network Intrusion Detection with Edge-Directed Graph Multi-Head Attention Networks. CoRR abs/2310.17348 (2023) - 2022
- [j8]Cangqi Zhou, Jing Zhang, Kaisheng Gao, Qianmu Li, Dianming Hu, Victor S. Sheng:
Bipartite network embedding with Symmetric Neighborhood Convolution. Expert Syst. Appl. 198: 116757 (2022) - [j7]Yanhui Peng, Jing Zhang, Cangqi Zhou, Shunmei Meng:
Knowledge Graph Entity Alignment Using Relation Structural Similarity. J. Database Manag. 33(1): 1-19 (2022) - [c13]Chen Hou, Cangqi Zhou, Chu-Ge Wu, Rui Cong, Kun Li:
Optimal Model of Cloud-Based Multi-Agent System for Trade-off Between Trustworthiness of Data and Cost of Data Usage. CASE 2022: 934-939 - [c12]Cangqi Zhou, Yuxiang Wang, Jing Zhang, Jiqiong Jiang, Dianming Hu:
End-to-end Modularity-based Community Co-partition in Bipartite Networks. CIKM 2022: 2711-2720 - [c11]Yuxiang Wang, Cangqi Zhou, Jing Zhang, Qianmu Li:
Attributed Graph Clustering with Double Contrastive Projector. IJCNN 2022: 1-8 - [c10]Cangqi Zhou, Sunyue Xu, Hao Ban, Jing Zhang:
Neural Topic Modeling with Gaussian Mixture Model and Householder Flow. PAKDD (2) 2022: 417-428 - [c9]Cangqi Zhou, Hui Chen, Jing Zhang, Qianmu Li, Dianming Hu:
AngHNE: Representation Learning for Bipartite Heterogeneous Networks with Angular Loss. WSDM 2022: 1470-1478 - 2021
- [j6]Cangqi Zhou, Hui Chen, Jing Zhang, Qianmu Li, Dianming Hu, Victor S. Sheng:
Multi-label graph node classification with label attentive neighborhood convolution. Expert Syst. Appl. 180: 115063 (2021) - [j5]Jing Zhang, Mengxi Li, Kaisheng Gao, Shunmei Meng, Cangqi Zhou:
Word and graph attention networks for semi-supervised classification. Knowl. Inf. Syst. 63(11): 2841-2859 (2021) - [c8]Mengxi Li, Jing Zhang, Lixia Chen, Yu Fu, Cangqi Zhou:
HPEMed: Heterogeneous Network Pair Embedding for Medical Diagnosis. ChineseCSCW (2) 2021: 364-375 - [c7]Cangqi Zhou, Jinling Shang, Jing Zhang, Qianmu Li, Dianming Hu:
Topic-Attentive Encoder-Decoder with Pre-Trained Language Model for Keyphrase Generation. ICDM 2021: 1529-1534 - [c6]Hui Chen, Cangqi Zhou, Jing Zhang, Qianmu Li:
Heterogeneous Graph Embedding Based on Edge-aware Neighborhood Convolution. IJCNN 2021: 1-8 - 2020
- [j4]Cangqi Zhou, Hao Ban, Jing Zhang, Qianmu Li, Yinghua Zhang:
Gaussian Mixture Variational Autoencoder for Semi-Supervised Topic Modeling. IEEE Access 8: 106843-106854 (2020) - [j3]Liang Feng, Qianchuan Zhao, Cangqi Zhou:
Improving performances of Top-N recommendations with co-clustering method. Expert Syst. Appl. 143 (2020) - [j2]Shuo Wang, Qianmu Li, Jun Hou, Shunmei Meng, Bo Zhang, Cangqi Zhou:
Active Defense by Mimic Association Transmission in Edge Computing. Mob. Networks Appl. 25(2): 725-742 (2020) - [c5]Yanhui Peng, Jing Zhang, Cangqi Zhou, Jian Xu:
Embedding-Based Entity Alignment Using Relation Structural Similarity. ICKG 2020: 123-130
2010 – 2019
- 2019
- [c4]Liang Feng, Qianchuan Zhao, Cangqi Zhou:
An efficient method to find communities in K-partite networks. ASONAM 2019: 534-535 - [c3]Shuo Wang, Qianmu Li, Shunmei Meng, Bo Zhang, Cangqi Zhou:
An Active Defense Model in Edge Computing Based on Network Topology Mimetic Correlation. MobiCASE 2019: 198-212 - [c2]Kaisheng Gao, Jing Zhang, Cangqi Zhou:
Semi-supervised Graph Embedding for Multi-label Graph Node Classification. WISE 2019: 555-567 - [i1]Kaisheng Gao, Jing Zhang, Cangqi Zhou:
Semi-Supervised Graph Embedding for Multi-Label Graph Node Classification. CoRR abs/1907.05743 (2019) - 2014
- [j1]Cangqi Zhou, Qianchuan Zhao:
Efficient Time Series Clustering and Its Application to Social Network Mining. J. Intell. Syst. 23(2): 213-229 (2014) - 2013
- [c1]Cangqi Zhou, Qianchuan Zhao, Ruixi Yuan:
An angle-based dissimilarity for accelerating the clustering of dynamic data in networks. ICNSC 2013: 199-204
Coauthor Index
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