Chung, Fu-lai Korris, Ph.D.
Research Interests: Machine Learning and AI, Data Mining and Big Data Analytics,
Computational Intelligence and Creativity
Upon receiving my M.Phil. and Ph.D. degrees from the Chinese University of Hong Kong and a B.Sc. degree from the University of Manitoba, I joined the Department of Computing, Hong Kong Polytechnic University and is now an associate professor. My primary research interests are in the study of intelligence, learning and recognition and their applications to a wide spectrum of tasks which involves text data (social media), time series (finance and stock) data, multimedia (image and video) data, network/graph data, bioinformatics data, etc. I published widely in prestige journals, including IEEE Transactions, ACM Transactions, and various AI/ML international journals, and also served on program committees of top international conferences.
Please contact me for the Hong Kong PhD Fellowship scheme's application details if you are interested in my research areas.
Currently, I'm working on deep transfer learning, adversarial learning, feature learning, social network analysis and mining, big data analytics and computational creativity. My Google scholar profile can be found here, my dblp computer science profile can be found here, and my Scopus profile can be found here and my ORCID is here. Here is a selected list of my recent journal and conference publications.
Newly accepted/published papers:
Xiao Shen, Quanyu Dai, Fu-lai Chung, Wei Lu and Kup-sze Choi, ‘Adversarial Deep Network Embedding for Cross-network Node Classification,’ accepted by AAAI’2020.
Jiaxin Chen, Liming Zhan, Xiaoming Wu and Fu-lai Chung, ‘Variational Metric Scaling for Metric-Based Meta-Learning’ accepted by AAAI’2020.
Xiao Shen, Sitong Mao, and Fu-lai Chung, ‘Cross-Network Learning with Fuzzy Labels for Seed Selection and Graph Sparsification in Influence Maximization,’ to appear in IEEE Trans. on Fuzzy Systems.
Wei Lu, Wenhao Jiang, Fu-lai Chung, Martin Ester and Wei Liu, 'A Deep Bayesian Tensor Based System for Video Recommendation,' ACM Trans. on Information Systems (ToIS), vol.37, no.1, 7:1-7:22, January 2019.
Wenhao Jiang, Hongchang Gao, Wei Lu, Wei Liu, Fu-lai Chung, and Heng Huang, 'Stacked Robust Adaptively Regularized Auto-regressions for Domain Adaptation, 'IEEE Trans. on Knowledge and Data Engineering (TKDE), 31(3), 561-574, March 2019.
Yumeng Guo, Fu-lai Chung, Guozheng Li, James C. Gee and Jiancong Wang, 'Leveraging Label Specific Discriminant Mapping Features for Multi-Label Learning,' ACM Transactions on Knowledge Discovery from Data (TKDD), 13(2), 24:1-24:23, May 2019.
Yuanpeng Zhang, Fu-lai Chung and Shitong Wang, 'A Multi-view & Multi-exemplar Fuzzy Clustering Approach: Theoretical Analysis and Experimental Studies,' IEEE Trans. on Fuzzy Systems (TFS), 27(8), 1543-1557, 2019.
Bin Qin, Fu-lai Chung, Shitong Wang, 'Biologically Plausible Fuzzy-Knowledge-Out and Its Induced Wide Learning of Interpretable TSK Fuzzy Classifiers,' to appear in IEEE Trans. on Fuzzy Systems (TFS).
Xiao Shen, and Fu-lai Chung, 'Deep Network Embedding for Graph Representation Learning in Signed Networks,' to appear in IEEE Trans. on Cybernetics (TCyb).
Wenlong Hang, Shuang Liang, Kup-sze Choi, Fu-lai Chung and Shitong Wang, 'Selective Transfer Classification Learning With Classification-Error-Based Consensus Regularization,' to appear in IEEE Transactions on Emerging Topics in Computational Intelligence.
Wenhao Jiang, Wei Lu, and Fu-lai Chung, “Knowledge Transfer for Spectral Clustering,” Pattern Recognition, vol.81, pp.484-496, 2018.
Xiaoqing Gu, Fu-lai Chung, and Shitong Wang, 'Fast Convex-hull Vector Machine for Training on Large-scale ncRNA Data Classification Tasks,' Knowledge Based System, vol.151, pp.149-164, 2018.
Sitong Mao, Xiao Shen, and Fu-lai Chung, 'Deep Domain Adaptation Based on Multi-layer Joint Kernelized Distance,' In Proceedings of the 41th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'18), 2018.
Wei Lu and Fu-lai Chung, 'A Deep Graphical Model for Layered Knowledge Transfer,” Proc. of Int. Conf. on Pattern Recognition, pp.260-265, 2018.
Xiao Shen and Fu-lai Chung, 'Deep Network Embedding with Aggregated Proximity Preserving,' Proceedings of the IEEE/ACM Int. Conf. on Social Network Analysis and Mining (ASONAM’17), pp.40-43, 2017.
Xiao Shen, Fu-lai Chung, and Sitong Mao, 'Leveraging Cross-Network Information for Graph Sparsification in Influence Maximization,' Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'17), 2017
Wenhao Jiang, Cheng Deng, Wei Liu, Feiping Nie, Fu-lai Chung, Heng Huang, 'Theoretic Analysis and Extremely Easy Algorithms for Domain Adaptive Feature Learning,' Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI’17), 2017.
Some other recent papers:
Wei Lu, Fu-lai Chung, Kunfeng Lai, Liang Zhang, “Recommender System Based on Scarce Information Mining,” Neural Networks, vol.93, pp.256-266, Sept. 2017.
Y. Jiang, Z. Deng, F.L. Chung, G. Wang, P. Qian, K.S. Choi, and S. Wang, “Recognition of Epileptic EEG Signals Using a Novel Multiview TSK Fuzzy System,” IEEE Trans. on Fuzzy Systems, vol.25, no.1, Feb. 2017.
Xiaoqing Gu, Fu-lai Chung, and Shitong Wang, 'Bayesian Takagi-Sugeno-Kang Fuzzy Classifier,' IEEE Trans. on Fuzzy Systems, vol.25, no.6, pp.1655-1671, Oct. 2017.
Ta Zhou, Fu-lai Chung, and Shitong Wang, 'Deep TSK Fuzzy Classifier with Stacked Generalization and Triplely Concise Interpretability Guarantee for Large Data,' IEEE Trans. on Fuzzy Systems, vol.25, no.5, pp.1207-1221, Oct. 2017.
Wei Lu, Fu-lai Chung, and Kunfeng Lai, 'Scarce Feature Topic Mining for Video Recommendation,' Proceedings of the 25th ACM Int. Conf. on Information and Knowledge Management (CIKM'16), Indianapolis, Indiana, USA: ACM, pp.1993-1996, 2016.
Wei Lu and Fu-lai Chung, 'Computational Creativity Based Video Recommendation,' Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'16), Pisa, Italy: ACM, pp.793-796, 2016.
Wenhao Jiang, Hongchang Gao, Fu-lai Chung, Heng Huang, 'The L2,1-Norm Stacked Robust Autoencoders for Domain Adaptation,' Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), pp.1723-1729, 2016.
Yumeng Guo, Fu-lai Chung, Guozheng Li, “An Ensemble Embedded Feature Selection Method for Multi-label Clinical Text Classification,” Proceedings of BIBM 2016, pp.823-826, 2016.
Zhaohong Deng, Yizhang Jiang, Fu-Lai Chung, Hisao Ishibuchi, Kup-Sze Choi, Shitong Wang, 'Transfer Prototype-based Fuzzy Clustering,' IEEE Trans. on Fuzzy Systems, vol.24, no.5, Oct. 2016.
Wenlong Hang, Fu-Lai Chung, Shitong Wang, 'Transfer Affinity Propagation-based Clustering,' Information Science, vol.348, pp.337-356, June 2016.
J. Wang, Z. Deng, K.S. Choi, Y. Jiang, X. Luo, F.L. Chung, Shitong Wang, 'Distance Metric Learning for Soft Subspace Clustering in Composite Kernel Space,' Pattern Recognition, vol.52, pp.113-134, April 2016.
C. Huang, Fu-lai Chung, and Shitong Wang, 'Multi-view L2-SVM and Its Multi-view Core Vector Machine,' Neural Networks, vol.75, pp.110-125, 2016.
Tongguang Ni, Fu-Lai Chung, Shitong Wang, 'Support Vector Machine with Manifold Regularization and Partially Labeling Privacy Protection, ' Information Science, vol.294, pp.390-407, Feb 2015.
Yizhang Jiang, Fu-lai Chung, Shitong Wang, Zhaohong Deng, Jun Wang, and Pengjiang Qian, 'Collaborative Fuzzy Clustering From Multiple Weighted Views,' IEEE Trans. on Cybernetics, vol.45, no.4, pp.688-701, April 2015.
Yingzhong Shi, Fu-lai Chung, Shitong Wang, 'An Improved TA-SVM Method Without Matrix Inversion and Its Fast Implementation for Nonstationary Datasets,' IEEE Trans. on Neural Networks and Learning Systems, vol.26, no.9, pp.2005-2018, 2015.
Terrence Leung and Fu-lai Chung, 'Persuasion Driven Influence Propagation in Social Networks, ' Proc. of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014), Beijing, China August 17-20, 2014
Wenhao Ying, Fu-lai Chung, and Shitong Wang, 'Scaling Up Synchronization-Inspired Partitioning Clustering, ' IEEE Trans. on Knowledge and Data Engineering, vol.26, no.8, pp.2045-2057, Aug 2014.
Shitong Wang, Jun Wang, and Fu-lai Chung, 'Kernel Density Kernel Density Estimation, Kernel Methods, and Fast Learning in Large Data Sets,' IEEE Trans. on Cybernetics, vol.44, no.1, January 2014.
Wenhao Jiang and Fu-lai Chung, 'A Trace Ratio Maximization Approach to Multiple Kernel-Based Dimensionality Reduction,' Neural Networks, vol.49, pp.96-106, Jan 2014.
Zhaohong Deng, Yizhang Jiang, Kup-Sze Choi, Fu-Lai Chung, Shitong Wang, 'Knowledge-Leverage Based TSK Fuzzy System Modeling,' IEEE Trans. on Neural Networks and Learning Systems, vol.24, no.8, pp.1200-1212, 2013.
Jun Wang, Fu-lai Chung, Shitong Wang, and Wenhao Ying, 'Weighted Spherical 1-Mean with Phase Shift and Its Application in ECG Discord Detection,' AI in Medicine, vol.57, no.1, pp.59-71, Jan. 2013.
The following list shows the classes that I have been teaching at PolyU in 2017-19.
o COMP4432 Machine Learning, Fall 2019 (for UG students)
o COMP4433 Data Mining and Data Warehousing, Fall 2019 (for UG students)