Следене
Chengqi Zhang
Chengqi Zhang
Professor of Information Technology
Потвърден имейл адрес: uts.edu.au
Заглавие
Позовавания
Позовавания
Година
A comprehensive survey on graph neural networks
Z Wu, S Pan, F Chen, G Long, C Zhang, SY Philip
IEEE transactions on neural networks and learning systems 32 (1), 4-24, 2020
75682020
Graph wavenet for deep spatial-temporal graph modeling
Z Wu, S Pan, G Long, J Jiang, C Zhang
arXiv preprint arXiv:1906.00121, 2019
15852019
Connecting the dots: Multivariate time series forecasting with graph neural networks
Z Wu, S Pan, G Long, J Jiang, X Chang, C Zhang
Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020
9702020
Adversarially regularized graph autoencoder for graph embedding
S Pan, R Hu, G Long, J Jiang, L Yao, C Zhang
arXiv preprint arXiv:1802.04407, 2018
8942018
Association Rule Mining: Models and Algorithms
C. Zhang, and S. Zhang
Lecture Notes in Computer Science LNAI 2307, 2002
832*2002
Data preparation for data mining
S Zhang, C Zhang, Q Yang
Applied artificial intelligence 17 (5-6), 375-381, 2003
8312003
Efficient mining of both positive and negative association rules
X Wu, C Zhang, S Zhang
ACM Transactions on Information Systems (TOIS) 22 (3), 381-405, 2004
8302004
Disan: Directional self-attention network for rnn/cnn-free language understanding
T Shen, T Zhou, G Long, J Jiang, S Pan, C Zhang
Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018
8192018
Network representation learning: A survey
D Zhang, J Yin, X Zhu, C Zhang
IEEE transactions on Big Data 6 (1), 3-28, 2018
7152018
Philip S Yu. A comprehensive survey on graph neural networks
Z Wu, S Pan, F Chen, G Long, C Zhang
arXiv preprint arXiv:1901.00596 5, 2019
6942019
Tri-party deep network representation
S Pan, J Wu, X Zhu, C Zhang, Y Wang
Network 11 (9), 12, 2016
5032016
Attributed graph clustering: A deep attentional embedding approach
C Wang, S Pan, R Hu, G Long, J Jiang, C Zhang
arXiv preprint arXiv:1906.06532, 2019
4322019
Learning graph embedding with adversarial training methods
S Pan, R Hu, S Fung, G Long, J Jiang, C Zhang
IEEE transactions on cybernetics 50 (6), 2475-2487, 2019
2762019
Genetic algorithm-based strategy for identifying association rules without specifying actual minimum support
X Yan, C Zhang, S Zhang
Expert Systems with Applications 36 (2), 3066-3076, 2009
2642009
Dynamic affinity graph construction for spectral clustering using multiple features
Z Li, F Nie, X Chang, Y Yang, C Zhang, N Sebe
IEEE transactions on neural networks and learning systems 29 (12), 6323-6332, 2018
2392018
Fedproto: Federated prototype learning across heterogeneous clients
Y Tan, G Long, L Liu, T Zhou, Q Lu, J Jiang, C Zhang
Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8432-8440, 2022
2232022
Compound Rank- Projections for Bilinear Analysis
X Chang, F Nie, S Wang, Y Yang, X Zhou, C Zhang
IEEE transactions on neural networks and learning systems 27 (7), 1502-1513, 2015
2232015
Federated learning for open banking
G Long, Y Tan, J Jiang, C Zhang
Federated Learning: Privacy and Incentive, 240-254, 2020
1882020
Support vector machines based on K-means clustering for real-time business intelligence systems
J Wang, X Wu, C Zhang
International Journal of Business Intelligence and Data Mining 1 (1), 54-64, 2005
1842005
Probabilistic exposure fusion
M Song, D Tao, C Chen, J Bu, J Luo, C Zhang
IEEE Transactions on Image Processing 21 (1), 341-357, 2011
1802011
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