劉胥影

個人經歷

Professional Activity

Journal Reviewer	IEEE Transactions on Knowledge and Data Engineering
	Data Mining and Knowledge Discovery
	Pattern Recognition
	Intelligent Data Analysis
	Journal of Computer Science and Technology
PC Member	AAAI'19, IJCAI'17/11, KDD'15, ICDM'18/15, SDM'13, PAKDD'16/13, ACML'15/14/12, CIDM'14, ACM SAC'15, etc.
Non-PC Reviewer	PAKDD'11, ACM'10

主講課程

Artificial Intelligence (18/17/16/15/14 Autumn)
C++ Programming Language (14/13/12/11 Spring)

學術成果

Book Chapters

X.-Y. Liuand Z.-H. Zhou. Ensemble methods for class imbalance learning (Chapter 4). In: H. He and Y. Ma (eds).Imbalanced Learning: Foundations, Algorithms, and Applications. IEEE Press Wiley, ISBN: 978-1118074626, 2013, 61-82.
Journal Papers
X.-Y. Liu, S.-T. Wang, M.-L. Zhang. Transfer synthetic over-sampling for class-imbalance learning with limited minority class data.Frontiers of Computer Science, 2018, accepted.
M.-L. Zhang, Y.-K. Li,X.-Y. Liu, X. Geng. Binary relevance for multi-label learning: An overview.Frontiers of Computer Science, 2018, 12(2): 191-202.
X.-Y. Liu, J. Wu, and Z.-H. Zhou.Exploratory undersampling for class-imbalance learning.IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, 2009, 39(2): 539-550. [code]
Z.-H. Zhou andX.-Y. Liu.On multi-class cost-sensitive learning.Computational Intelligence, 2010, 26(3): 232-257. [code]
Z.-H. Zhou andX.-Y. Liu.Training cost-sensitive neural networks with methods addressing the class imbalance problem.IEEE Transactions on Knowledge and Data Engineering (TKDE), 2006, 18(1): 63-77. [code]
X. Ding, C.-C. Cao,X.-Y. Liu, etc. HSS-Bin: An unsupervised metagenomic binning method based on hybrid sequence feature recognition and spectral clustering.Current Bioinformatics, 2016, 11(3): 330-339.
Conference Papers
S.-Y. Ding,X.-Y. Liuand M.-L. Zhang.Imbalanced augmented class learning with unlabeled data by label confidence propagation. In:Proceedings of the 18th IEEE International Conference on Data Mining (ICDM'18), Singapore, 2018. (full paper) [code]
M.-L. Zhang, B.-B. Zhou,X.-Y. Liu. Partial label learning via feature-aware disambiguation. In:Proceedings of the 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'16), San Francisco, CA, 2016, 1335-1344.
M.-L Zhang, Y.-K Li,X.-Y Liu. Towards class-imbalance aware multi-label learning. In:Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI’15), 2015, Buenos Aires, Argentina, 2015, 4041-4047.
X.-Y. Liu, and Q.-Q. Li. Learning from combination of data chunks for multi-class imbalanced data. In:Proceedings of 2014 International Joint Conference on Neural Networks (IJCNN’14), Beijing, China, 2014.
X.-Y. Liu, Q.-Q. Li and Z.-H. Zhou. Learning imbalanced multi-class data with optimal dichotomy weights. In:Proceedings of the 13th IEEE International Conference on Data Mining (ICDM'13), Dallas, TX, 2013, 478-487.
X.-Y. Liuand Z.-H. Zhou.Learning with cost intervals. In:Proceedings of the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'10), Washington, DC, 2010, pp.403-412. [code]
X.-Y. Liu, J. Wu, and Z.-H. Zhou.Exploratory under-sampling for class-imbalance learning. In:Proceedings of the 6th IEEE International Conference on Data Mining (ICDM'06), Hong Kong, China, 2006, pp.965-969. [code]
X.-Y. Liuand Z.-H. Zhou.The influence of class imbalance on cost-sensitive learning: An empirical study. In:Proceedings of the 6th IEEE International Conference on Data Mining (ICDM'06), Hong Kong, China, 2006, pp.970-974.
Z.-H. Zhou andX.-Y. Liu.On multi-class cost-sensitive learning. In:Proceedings of the 21st National Conference on Artificial Intelligence (AAAI'06), Boston, MA, 2006, pp.567-572. [code]
Y. Yu, D.-C. Zhan,X.-Y. Liu, M. Li, and Z.-H. Zhou.Predicting future customers via ensembling gradually expanded trees.International Journal of Data Warehousing and Mining, 2007, 3(2): 12-21.Invited paper for the PAKDD'06 Data Mining Competition (Open Category) Grand Champion Team.

劉胥影

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