Xin Yao's Research Interests: Neural Network Ensembles

Neural network ensembles have been shown to perform better in terms of generalisation for many problems. I am interested in the issue of how to design and train a neural network ensemble so that individual networks are cooperative with each other. The idea is to have different individuals learn diferent things so that the whole ensemble can learn the overall task better. In particular, I am keen on negative correlation, boosting and bagging.

Selected Papers

  1. G. Brown, X. Yao, J. Wyatt, H. Wersing and B. Sendhoff, ``Exploiting Ensemble Diversity for Automatic Feature Extraction,'' Proc. of the 9th International Conference on Neural Information Processing (ICONIP'02), pp.1786-1790, Singapore, November 2002.

  2. Y. Liu and X. Yao, ``Learning and Evolution by Minimization of Mutual Information,'' Proc. of the 7th International Conference on Parallel Problem Solving from Nature (PPSN VII), Lecture Notes in Computer Science, Vol. 2439, Springer, September 2002, pp.495-504.

  3. Y. Liu, X. Yao, Q. Zhao and T. Higuchi, ``An experimental comparison of neural network ensemble learning methods on decision boundaries,'' Proceedings of the 2002 International Joint Conference on Neural Networks (IJCNN'02), pp.221-226, IEEE Press, Piscataway, NJ, USA, 12-17 May 2002.

  4. X. Yao and Y. Liu, ``From evolving a single neural network to evolving neural network ensembles,'' In Advances in the Evolutionary Synthesis of Intelligent Agents, Mukesh J. Patel, Vasant Honavar and Karthik Balakrishnan (eds.), Chapter 14, pp.383-427, The MIT Press, Cambridge, MA, 2001. (ISBN 0-262-16201-6)

  5. Y. Liu, X. Yao and T. Higuchi, ``Evolutionary Ensembles with Negative Correlation Learning,'' IEEE Transactions on Evolutionary Computation, 4(4):380-387, November 2000.
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  6. Y. Liu and X. Yao, ``Ensemble learning via negative correlation,'' Neural Networks, 12(10):1399-1404, December 1999.
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  7. Y. Liu and X. Yao, ``Simultaneous training of negatively correlated neural networks in an ensemble,'' IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 29(6):716-725, December 1999.

  8. 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.

Last update: 5 September 2000