Publications

Refereed Journal Papers

[1] Y. He, R. Liu, H. Li, S. Wang and X. Lu, "Short-term power load probability density forecasting method using kernel-based support vector quantile regression and Copula theory", Applied Energy 185, pp. 254-266, 2017. [pdf]

[2] Y. Sun, K. Tang, L.L.Minku, S. Wang and X. Yao, "Online Ensemble Learning of Data Streams with Gradually Evolved Classes", IEEE Transactions on Knowledge and Data Engineering, 28(6):1532 - 1545, 2016. [pdf]

[3] Yuwei Guo, Licheng Jiao, Shuang Wang, Shuo Wang, Fang Liu, Kaixuan Rong and Tao Xiong, "A novel dynamic rough subspace based selective ensemble", Pattern Recognition, DOI: 10.1016/j.patcog.2014.11.001. [pdf]

[4] S. Wang, L.L.Minku and X. Yao, "Resampling-Based Ensemble Methods for Online Class Imbalance Learning", IEEE Transactions on Knowledge and Data Engineering, 27(5):1356-1368, 2015. [pdf]

Code is available [here] in Java (Weka 3.7 required).

[5] Ronghua Shang, Yuying Wang, Jia Wang, Licheng Jiao, Shuo Wang and Liping Qi, "A Multi-population Cooperative Coevolutionary Algorithm for Multi-objective Capacitated Arc Routing Problem", Information Sciences, March 2014, Accepted.

[6] S. Wang, L.L.Minku and X. Yao, "Online Class Imbalance Learning and Its Applications in Fault Detection", Special Issue of International Journal of Computational Intelligence and Applications, 12(4):1340001(1-19),2013. [pdf]

[7] S. Wang and X. Yao, "Using Class Imbalance Learning for Software Defect Prediction", IEEE Transactions on Reliability, 62(2):434-443, 2012.

PDF is available [here].

Code is available [here] in Java (weka 3.7 required).

[8] S. Wang and X. Yao, "Multi-Class Imbalance Problems: Analysis and Potential Solutions", IEEE Transactions on Systems, Man and Cybernetics, PartB: Cybernetics, 42(4):1119-1130, August 2012.

Available [here] or [online].

Code is available [here] in Java (weka 3.7 required).

[9] S. Wang and X. Yao, "Relationships Between Diversity of Classification Ensembles and Single-Class Performance Measures", IEEE Transactions on Knowledge and Data Engineering, 25(1):206-219, January 2013.

Available [here] or [online].

Code is available [here] in Java (Weka 3.4 required).

PhD Thesis

Shuo Wang. Ensemble Diversity for Class Imbalance Learning. School of Computer Science, The University of Birmingham. Information is available [here].

Refereed Conferences and Workshops

[1] S.Wang, L.L.Minku, and X.Yao. Dealing with Multiple Classes in Online Class Imbalance Learning. In the 25th International Joint Conference on Artificial Intelligence (IJCAI'16). Pages 2118-2124, 2016. [pdf]

Code is available [here] in Java (Weka 3.7 and moa201208 required).

[2] S.Wang, L.L.Minku, and X.Yao. A Multi-Objective Ensemble Method for Online Class Imbalance Learning. In International Joint Conference on Neural Networks (IJCNN '14). Pages 3311-3318, 2014. [pdf]

[3] S.Wang, L.L.Minku, D.Ghezzi, D.Caltabiano, P.Tino and X.Yao (04/2013). Concept Drift Detection for Online Class Imbalance Learning. In International Joint Conference on Neural Networks (IJCNN '13). 1-10, 2013. [pdf]

[4] S.Wang, L.L.Minku and X.Yao (01/2013). A Learning Framework for Online Class Imbalance Learning. IEEE Symposium Series on Computational Intelligence (SSCI) 2013, Singapore. Pages 36-45, 2013. [pdf]

[5] S.Wang and X.Yao (07/2010). The Effectiveness of A New Negative Correlation Learning Algorithm for Classification Ensembles. IEEE International Conference on Data Mining Workshops 2010, Sydney, Australia. Pages 1013-1020, 2010. [pdf]

[6] S.Wang and H.Chen and X.Yao (02/2010). Negative Correlation Learning for Classification Ensembles. International Joint Conference on Neural Networks 2010, Barcelona, Spain. Pages 2893-2900, 2010. (Travel Grant Awarded)[pdf]

[7] S.Wang and X.Yao (07/2009). Theoretical Study of the Relationship Between Diversity and Single-Class Measures for Class Imbalance Learning. IEEE International Conference on Data Mining Workshops 2009, Miami, Florida, USA. Pages 76-81, 2009. [pdf]

[8] S.Wang and K.Tang and X.Yao (01/2009). Diversity Exploration and Negative Correlation Learning on Imbalanced Data Sets. International Joint Conference on Neural Networks 2009, Atlanta, Georgia, USA. Pages 3259-3266, 2009. (Travel Grant Awarded) [pdf]

[9] S.Wang and X.Yao (12/2008). Diversity Analysis on Imbalanced Data Sets by Using Ensemble Models. IEEE Symposium on Computational Intelligence and Data Mining 2009, Nashville, TN, USA. Pages 324-331, 2009. [pdf]

Research Progress Reports

RSMG Report 4: Class Imbalance Learning (March 2009) [pdf]

RSMG Report 3: Class Imbalance Learning (August 2008) [pdf]

Other Documents

Wang, S. (2006). Design and Materialize Software of Mobile terminal by Ambient Intelligence Systems. Electronic Engineering and Product World, 2006 (15) [html]