Representative Publications

Supervised Learning

Multiple Experts and Classifier Combination

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• Lei Xu and Shun-ichi Amari (2008), “Combining Classifiers and Learning Mixture-of-Experts” in Encyclopedia of Artificial Intelligence, Edited By: Juan Ramón, Rabuñal Dopico; Julian Dorado; Alejandro Pazos, IGI Global (IGI) publishing company, pp318-326
• Lei Xu (2001), ``Best Harmony, Unified RPCL and Automated Model Selection for Unsupervised and Supervised Learning on Gaussian Mixtures, ME-RBF Models and Three-Layer Nets ", International Journal of Neural Systems, Vol.11, No.1, pp3-69, 2001.
• Lei Xu, M.I.Jordan & G. E. Hinton (1995), `` An Alternative Model for Mixtures of Experts", Advances in Neural Information Processing Systems 7, eds., Cowan, J.D., Tesauro, G., and Alspector, J., MIT Press, Cambridge MA, 1995, pp633-640.
• Lei Xu, Adam Krzyzak & Ching Y. Suen, (1994), `` Associative Switch for Combining Multiple Classifiers", Journal of Artificial Neural Networks, Vol.1, No.1, pp77-100, 1994.
• Lei Xu, Adam Krzyzak and Ching Y. Suen, (1992), `` Several Methods for Combining Multiple Classifiers and Their Applications in Handwritten Character Recognition", IEEE Trans. on System, Man and Cybernetics, Vol. SMC-22, No.3, pp418-435, 1992.
• M.I.Jordan & Lei Xu (1995), `` Convergence results for the EM approach to mixtures-of-experts architectures'', Neural Networks, Vol.8, No.9, pp1409-1431, the Joint official Journal of International Neural Network Society, European Neural Network Society and Japanese Neural Network Society.
• Ke Chen, Lei Xu , and Huishen Chi (1999), ``Improved Learning Algorithms for Mixture of Experts in Multiclass Classification", Neural Networks, Vol. 12, pp1229-1252,1999.

Radial Basis Function Nets

• Lei Xu (2009), "Learning Algorithms for RBF Functions and Subspace Based Functions", Ch.3 in "Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods and Techniques", eds. by Olivas, Guerrero, Sober, Benedito, & Lopez, IGI Global publication, pp60-94.
• Lei Xu (2001), ``Best Harmony, Unified RPCL and Automated Model Selection for Unsupervised and Supervised Learning on Gaussian Mixtures, ME-RBF Models and Three-Layer Nets ", International Journal of Neural Systems, Vol.11, No.1, pp3-69, 2001.
• Lei Xu (1998a), ``RBF Nets, Mixture Experts, and Bayesian Ying-Yang Learning", Neurocomputing, Vol. 19, No.1-3, pp223-257, 1998.
• Lei Xu, A. Krzyzak & A.L. Yuille, (1994), "On Radial Basis Function Nets and Kernel Regression: Statistical Consistency, Convergence Rates and Receptive Field Size", Neural Networks, (the same as the above), Vol.7, No.4, pp609-628, 1994.
• See also the 2nd item in Bayesian Ying-Yang Learning System and Theory.
• Lei Xu (1998), ``Adaptive RBF Net Algorithms for Nonlinear Signal Learning with Applications to Financial Prediction and Investment", Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP98), May 12-15, 1998, Seattle, WA, Vol. 2, pp1153-1156.
• Adam Krzyzak and Lei Xu (1996), `` Optimal Radial basis Function Nets with application to Nonlinear Function Learning and Classification", Progress in Neural Information Processing: Proc. Intl Conf. on Neural Information Processing (ICONIP96), Sept. 24-27, 1996, pp271-274, Springer-verlag.

Feed-forward Networks

• Lei Xu (2003), `` BYY learning, regularized implementation, and model selection on modular networks with one hidden layer of binary units ", Neurocomputing, Vol. 51, pp 277-301, 2003. Errata to this paper is given here , which is published on Neurocomputing, Vol. 55, pp 405-406, 2003.
• Ouyang Ning, Wing-kai Lam, K. Yamauchi and Lei Xu (1999), ``Using An Improved Back Propagation Learning Method to Diagnose The Sites of Cardiac Hypertrophy", MD Computing, Vol. 16, No.1, pp79-81, 1999.
• Lei Xu, S.Klasa & A.L. Yuille, (1992), ``Recent Advances on Techniques Static Feed-forward Networks with Supervised Learning", International Journal of Neural Systems, Vol.3, No.3, 1992, pp253-290.