Xin Yao's Research Interests: Machine Learning and Data Mining


I've been working on ensemble learning since late 1990s, especially on negative correlation learning:

  1. Y. Liu and X. Yao, ``Negatively correlated neural networks can produce best ensembles,'' Australian Journal of Intelligent Information Processing Systems, 4(3/4):176-185, 1997.

  2. Y. Liu and X. Yao, ``Ensemble learning via negative correlation,'' Neural Networks, 12(10):1399-1404, December 1999.
    Available from Elsevier's journal site as a PDF file.

Later on, I've introduced multi-objective learning into ensemble learning due to their natural matach:

  1. A Chandra and X. Yao, ``Ensemble learning using multi-objective evolutionary algorithms,'' Journal of Mathematical Modelling and Algorithms, 5(4):417-445, December 2006.
    Available as a PDF file.

  2. H. Chen and X. Yao, ``Multiobjective Neural Network Ensembles based on Regularized Negative Correlation Learning,'' IEEE Transactions on Knowledge and Data Engineering, 22(12):1738-1751, December 2010.

In recent years, I have been focusing on class imbalance learning:

  1. 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, May 2015.

  2. U. Bhowan, M. Johnston, M. Zhang and X. Yao, ``Reusing Genetic Programming for Ensemble Selection in Classification of Unbalanced Data,'' IEEE Transactions on Evolutionary Computation, 18(6):893-908, December 2014.
    Preprint is available.

  3. S. Wang, L. Minku and X. Yao, ``Online class imbalance learning and its applications in fault detection,'' International Journal of Computational Intelligence and Applications, 12(4):1340001 (19 pages), December 2013.

  4. U. Bhowan, M. Johnston, M. Zhang and X. Yao, ``Evolving Diverse Ensembles using Genetic Programming for Classification with Unbalanced Data,'' IEEE Transactions on Evolutionary Computation, 17(3):368-386, June 2013.
    Preprint is available.

  5. M. Lin, K. Tang and X. Yao, ``A Dynamic Sampling Approach to Training Neural Networks for Multi-class Imbalance Classification,'' IEEE Transactions on Neural Networks and Learning Systems, 24(4):647-660, April 2013.

  6. S. Wang and X. Yao, ``Using Class Imbalance Learning for Software Defect Prediction,'' IEEE Transactions on Reliability, 62(2):434-443, June 2013.
    Also available here.

  7. 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.
    Preprint is available.

  8. S. Wang and X. Yao, ``Multi-Class Imbalance Problems: Analysis and Potential Solutions,'' IEEE Transactions on Systems, Man and Cybernetics, Part B, 42(4):1119-1130, August 2012.
    Preprint is available.

and on online learning:

  1. 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, accepted on 27/1/2016.

  2. H. Chen, P. Tino, A. Rodan and X. Yao, ``Learning in the Model Space for Cognitive Fault Diagnosis,'' IE EE Transactions on Neural Networks and Learning Systems, 25(1):124-136, January 2014.

  3. L. L. Minku and X. Yao, "DDD: A New Ensemble Approach For Dealing With Concept Drift,'' IEEE Transactions on Knowledge and Data Engineering, 24(4):619-633, April 2012.
    Also available here.

  4. L. L. Minku, A. White and X. Yao, ``The Impact of Diversity on On-line Ensemble Learning in the Presence of Concept Drift,'' IEEE Transactions on Knowledge and Data Engineering, 22(5):730-742, May 2010.
    Also available here.

  5. K. Tang, M. Lin, F. L. Minku and X. Yao, ``Selective Negative Correlation Learning Approach to Incremental Learning,'' Neurocomputing, 72(13-15):2796-2805, August 2009.
    Let me know if you want a soft copy.

I'm interested in several different data mining tasks, e.g., fraud detection, classification, rule discovery, data warehousing, etc.:

  1. M. Salim and X. Yao, ``Evolving SQL Queries for Data Mining,'' Proc. of the Third International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'02), Lecture Notes in Computer Science, Vol. 2412, Springer, August 2002, pp.62-67.
    Available from Springer's web site as a PDF file.

  2. C. Zhang, X. Yao and J. Yang, ``An Evolutionary Approach to Materialized Views Selection in a Data Warehouse Environment,'' IEEE Transactions on Systems, Man and Cybernetics, Part C, 31(3):282-294, August 2001.
    Available as a gzipped ps file.

  3. H. He, S. Hawkins, W. Graco, and X. Yao, ``Application of Genetic Algorithm and K-Nearest Neighbour Method in Real World Medical Fraud Detection Problem,'' Journal of Advanced Computational Intelligence, 4(2):130-137, 2000.