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TFC: Transformer Fused Convolution for Adversarial Domain Adaptation Journal article
Wang, Mengzhu, Chen, Junyang, Wang, Ye, Gong, Zhiguo, Wu, Kaishun, Leung, Victor C.M.. TFC: Transformer Fused Convolution for Adversarial Domain Adaptation[J]. IEEE Transactions on Computational Social Systems, 2024, 11(1), 697-706.
Authors:  Wang, Mengzhu;  Chen, Junyang;  Wang, Ye;  Gong, Zhiguo;  Wu, Kaishun; et al.
Favorite | TC[WOS]:1 TC[Scopus]:3  IF:4.5/4.6 | Submit date：2024/02/22
Convolutional Neural Networks (Cnns)  Transfer Fused Convolution  Unsupervised Domain Adaptation (Uda)  Vision Transform  
Joint Adversarial Domain Adaptation With Structural Graph Alignment Journal article
Wang, Mengzhu, Chen, Junyang, Wang, Ye, Wang, Shanshan, Li, Lin, Su, Hao, Gong, Zhiguo, Wu, Kaishun, Chen, Zhenghan. Joint Adversarial Domain Adaptation With Structural Graph Alignment[J]. IEEE Transactions on Network Science and Engineering, 2024, 11(1), 604-612.
Authors:  Wang, Mengzhu;  Chen, Junyang;  Wang, Ye;  Wang, Shanshan;  Li, Lin; et al.
Favorite | TC[WOS]:3 TC[Scopus]:3  IF:6.7/6.0 | Submit date：2024/02/22
Conditional Distribution  Joint Adversarial Domain Adaptation  Joint Distribution  Marginal Distribution  Structural Graph Alignment  
IRLM: Inductive Representation Learning Model for Personalized POI Recommendation Journal article
Chen, Junyang, Wang, Mengzhu, Zhang, Haodi, Xu, Zhenghua, Li, Xueliang, Gong, Zhiguo, Wu, Kaishun, Leung, Victor C.M.. IRLM: Inductive Representation Learning Model for Personalized POI Recommendation[J]. IEEE Transactions on Computational Social Systems, 2023, 10(5), 2827-2836.
Authors:  Chen, Junyang;  Wang, Mengzhu;  Zhang, Haodi;  Xu, Zhenghua;  Li, Xueliang; et al.
Favorite | TC[WOS]:2 TC[Scopus]:2  IF:4.5/4.6 | Submit date：2023/01/30
Inductive Representation Learning  Location-based Social Network (Lsbn)  Poi Recommendation  Smart Cities  Representation Learning  Feature Extraction  Trajectory  Training  Standards  Social Networking (Online)  Smart Cities  
Towards Robust Task Assignment in Mobile Crowdsensing Systems Journal article
Wang, Liang, Yu, Zhiwen, Wu, Kaishun, Yang, Dingqi, Wang, En, Wang, Tian, Mei, Yihan, Guo, Bin. Towards Robust Task Assignment in Mobile Crowdsensing Systems[J]. IEEE Transactions on Mobile Computing, 2023, 14(8).
Authors:  Wang, Liang;  Yu, Zhiwen;  Wu, Kaishun;  Yang, Dingqi;  Wang, En; et al.
Favorite | TC[WOS]:11 TC[Scopus]:14  IF:7.7/6.5 | Submit date：2022/05/17
Mobile Crowdsensing  Task Assignment  Robustness  Evolutionary Algorithms  
Adversarial Caching Training: Unsupervised Inductive Network Representation Learning on Large-Scale Graphs Journal article
Junyang Chen, Zhiguo Gong, Wei Wang, Cong Wang, Zhenghua Xu, Jianming Lv, Xueliang Li, Kaishun Wu, Weiwen Liu. Adversarial Caching Training: Unsupervised Inductive Network Representation Learning on Large-Scale Graphs[J]. IEEE Transactions on Neural Networks and Learning Systems, 2022, 33(12), 7079-7090.
Authors:  Junyang Chen;  Zhiguo Gong;  Wei Wang;  Cong Wang;  Zhenghua Xu; et al.
Favorite | TC[WOS]:19 TC[Scopus]:16  IF:10.2/10.4 | Submit date：2023/01/30
Adversarial Learning  Graph Neural Network  Inductive Learning  Negative Sampling (Ns)  Network Embedding  
Self-Training Enhanced: Network Embedding and Overlapping Community Detection With Adversarial Learning Journal article
Chen, Junyang, Gong, Zhiguo, Mo, Jiqian, Wang, Wei, Wang, Wei, Wang, Cong, Dong, Xiao, Liu, Weiwen, Wu, Kaishun. Self-Training Enhanced: Network Embedding and Overlapping Community Detection With Adversarial Learning[J]. IEEE Transactions on Neural Networks and Learning Systems, 2022, 33(11), 6737-6748.
Authors:  Chen, Junyang;  Gong, Zhiguo;  Mo, Jiqian;  Wang, Wei;  Wang, Wei; et al.
Favorite | TC[WOS]:17 TC[Scopus]:16  IF:10.2/10.4 | Submit date：2022/12/01
Adversarial Learning  Network Embedding (Ne)  Overlapping Community Detection  Self-training  
A Simple yet Effective Layered Loss for Pre-training of Network Embedding Journal article
Chen, Junyang, Li, Xueliang, Li, Yuanman, Li, Paul, Wang, Mengzhu, Zhang, Xiang, Gong, Zhiguo, Wu, Kaishun, Leung, Victor C.M.. A Simple yet Effective Layered Loss for Pre-training of Network Embedding[J]. IEEE Transactions on Network Science and Engineering, 2022, 9(3), 1827 - 1837.
Authors:  Chen, Junyang;  Li, Xueliang;  Li, Yuanman;  Li, Paul;  Wang, Mengzhu; et al.
Favorite | TC[WOS]:6 TC[Scopus]:3  IF:6.7/6.0 | Submit date：2022/05/17
Graph Neural Networks  Layered Loss  Network Embedding  Pre-training Of Unlabeled Nodes  
Meta-path Based Neighbors for Behavioral Target Generalization in Sequential Recommendation Journal article
Chen, Junyang, Gong, Zhiguo, Li, Yuanman, Zhang, Huanjian, Yu, Hongyong, Zhu, Junzhang, Fan, Ge, Wu, Xiao Ming, Wu, Kaishun. Meta-path Based Neighbors for Behavioral Target Generalization in Sequential Recommendation[J]. IEEE Transactions on Network Science and Engineering, 2022, 9(3), 1658-1667.
Authors:  Chen, Junyang;  Gong, Zhiguo;  Li, Yuanman;  Zhang, Huanjian;  Yu, Hongyong; et al.
Favorite | TC[WOS]:15 TC[Scopus]:19  IF:6.7/6.0 | Submit date：2022/05/17
Behavioral Target Generalization  Sequential Recommendation  Ctr Prediction  Recommender Systems  
Wi-Fi Radar: Recognizing Human Behavior with Commodity Wi-Fi Journal article
Zou, Yongpan, Liu, Weifeng, Wu, Kaishun, Ni, Lionel M.. Wi-Fi Radar: Recognizing Human Behavior with Commodity Wi-Fi[J]. IEEE COMMUNICATIONS MAGAZINE, 2017, 55(10), 105-111.
Authors:  Zou, Yongpan;  Liu, Weifeng;  Wu, Kaishun;  Ni, Lionel M.
Favorite | TC[WOS]:25 TC[Scopus]:44  IF:8.3/9.4 | Submit date：2018/10/30
Simulation and Experimentation Platforms for Underwater Acoustic Sensor Networks: Advancements and Challenges Journal article
Luo, Hanjiang, Wu, Kaishun, Ruby, Rukhsana, Hong, Feng, Guo, Zhongwen, Ni, Lionel M.. Simulation and Experimentation Platforms for Underwater Acoustic Sensor Networks: Advancements and Challenges[J]. ACM COMPUTING SURVEYS, 2017, 50(2).
Authors:  Luo, Hanjiang;  Wu, Kaishun;  Ruby, Rukhsana;  Hong, Feng;  Guo, Zhongwen; et al.
Favorite | TC[WOS]:47 TC[Scopus]:65  IF:23.8/21.1 | Submit date：2018/10/30
Underwater Acoustic Sensor Networks  Experiment  Simulators  Testbeds