Representative Publications

Unsupervised Learning

  • Shikui TU and Lei Xu (2012), “A theoretical investigation of several model selection criteria for dimensionality reduction,” Pattern Recognition Letters , Vol.33:pp1117-1126, 2012.
  • Lei Xu (2012), " On essential topics of BYY harmony learning: Current status, challenging issues, and gene analysis applications",  A special issue on Machine learning and intelligence science: IScIDE (C), Journal of Frontiers of Electrical and Electronic Engineering 7(1) (2012) 147–196.
  • Lei Xu (2011), "Another perspective of BYY harmony learning: representation in multiple layers, co-decomposition of data covariance matrices, and applications to network biology. A special issue on Machine learning and intelligence science: IScIDE2010 (A), Journal of Frontiers of Electrical and Electronic Engineering in China 6(1) (2011) 86–119.
  • Lei Xu (2010), "Bayesian Ying-Yang system, best harmony learning, and five action circling", A special issue on Emerging Themes on Information Theory and Bayesian Approach, Journal of Frontiers of Electrical and Electronic Engineering in China, 5(3):281–328, 2010.
  • Lei Xu  (2008),  “Independent Subspaces”  in Encyclopedia of Artificial Intelligence,  Edited By: Juan Ramón, Rabuñal Dopico; Julian Dorado; Alejandro Pazos,  IGI Global (IGI)  publishing company,  pp903-912.
  • Lei Xu (2007),  A unified perspective on advances of independent subspaces: basic, temporal, and local structures, Proc.6th.Intel.Conf.Machine Learning and Cybernetics, Hong Kong, 19-22 Aug.2007, 767-776.
  • Lei Xu ,(2001) ``An Overview on Unsupervised Learning from Data Mining Perspective", Advances in Self-Organizing Maps, Nigel Allison, et al eds, Springer-Verlag, pp181-210, 2001.

Least MSE Reconstruction, PCA, MCA and Nonlinear Extensions

  • Lei Xu, (2003), ``Independent Component Analysis and Extensions with Noise and Time: A Bayesian Ying-Yang Learning Perspective ", Neural Information Processing - Letters and Reviews, Vol.1, No.1, pp1-52, 2003.
  • Lei Xu(1998b), ``Bayesian Kullback Ying-Yang Dependence Reduction Theory ", Neurocomputing, Vol.22, No.1-3, a special issue on Independence and artificial neural networks , pp81-112, 1998.
  • Lei Xu(1998c), ``Bayesian Ying-Yang Dimension Reduction and Determination", Journal of Computational Intelligence in Finance, Vol.6, No.5, a special issue on Complexity and Dimensionality Reduction in Finance . pp6-18, 1998.
  • Lei Xu (1993), "Least MSE Reconstruction: A Principle for Self-Organizing Nets", Neural Networks, the Joint official Journal of International Neural Network Society, European Neural Network Society and Japanese Neural Network Society, Vol. 6, pp. 627-648, 1993.    
  • Its preliminary version was partially given on "Least MSE Reconstruction for Self-Organization: (I)&(II) ", Proc. of 1991 International Joint Conference on Neural Networks, Singapore, Nov., 1991, pp2363-2373.
  • Lei Xu & A.L. Yuille (1995), "Robust Principal Component Analysis by Self-Organizing Rules Based on Statistical Physics Approach", IEEE Trans. on Neural Networks, regular paper, Vol.6, No.1, Jan, 1995, pp131-143.
  • Its preliminary version was partially given on Proc. of 1992 IEEE-INNS Intl. Joint Conf. on Neural Networks (IJCNN92), June 7-11, 1992, Baltimore, MA, Vol. I, pp.812-817.
  • Lei Xu, E.Oja & C.Y.Suen, (1992), `` Modified Hebbian Learning for Curve and Surface Fitting ", Neural Networks, the Joint official Journal of International Neural Network Society, European Neural Network Society and Japanese Neural Network Society, Vol.5, 1992, pp441-457.
  • Lei Xu, A. Krzyzak and E.Oja, (1991), `` A Neural Net for Dual Subspace Pattern Recognition Methods", International Journal of Neural Systems, Vol.2, No.3, 1991, pp169-184.
  • Bailing Zhang, Lei Xu and Minyue Fu (1996), ``Learning Multiple Causes by Competition Enhanced Least Mean Square Error Reconstruction", International Journal of Neural Systems, Vol.7, No.3, pp223-236.
  • Lei Xu (1995), `` Vector Quantization by Local and Hierarchical LMSER", Proc. of 1995 Intl Conf. on Artificial Neural Networks, Paris, France, Oct.9-13, 1995, Vol.II, 575-579.
  • Lei Xu(1994), `` Beyond PCA Learnings: From Linear to Nonlinear and From Global Representation to Local Representation ", Proceedings of International Conference on Neural Information Processing, Invited Paper, Oct 17-20, Seuol, Korea, 1994, pp943-949.
  • Lei Xu (1994), `` Theories for Unsupervised Learning: PCA and Its Nonlinear Extensions", Proceedings of IEEE International Conference on Neural Networks 1994, Invited Paper, June 26-July 2, Orlando, Florida, Vol.II, pp1252-1257.

Competitive Learning, Clustering analysis, and Object Detection

·        Lei Xu (2007), Rival Penalized Competitive Learning,  In Scholarpedia, no. 19850, http://scholarpedia.org, 2007.

  • Lei Xu (2007), `` A unified perspective  and new results on RHT computing, mixture based learning, and multi-learner based problem solving ",  Pattern Recognition,  (40) 2129–2153.
  • Lei Xu (2002), ``BYY harmony learning, structural RPCL, and topological self-organizing on mixture models", Neural Networks, Vol. 15, pp1125-1151, 2002.
  • 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, A. Krzyzak & E.Oja, (1993), "Rival Penalized Competitive Learning for Clustering Analysis, RBF net and Curve Detection", IEEE Trans. on Neural Networks, Vol.4, No.4, pp636-649, 1993, regular paper.
  • Lei Xu (1998) , ``Rival Penalized Competitive Learning, Finite Mixture, and Multisets Clustering", Proc. Intentional Joint Conference on Neural Networks, Vol., May 5-9, 1998, Anchorage, Alaska.
  • Lei Xu (1995), `` A Unified Learning Framework: Multisets Modeling Learning", Proceedings of World Congress On Neural Networks, Invited Paper, July 17-21, 1995, Washington, DC, Vol.I, pp35-42.
  • Lei Xu (1994), ``Multisets Modeling Learning: An Unified Theory for Supervised and Unsupervised Learning", Proc. of 1994 IEEE International Conference on Neural Networks (ICNN94), Invited Paper, June 26-July 2, 1994,, Orlando, Florida, Vol.I, pp.315-320.
  • Lei Xu (1990), `` Adding Learned Expectation into The Learning Procedure of Self-Organizing Maps", International Journal of Neural Systems, Vol.1, No.3, 1990, pp269-283.
  • Lei Xu, (2003), ``Data smoothing regularization, multi-sets-learning, and problem solving strategies", Neural Networks, Vol. 16, pp817¨C825, 2003.
  • Shi L, Wang P., Liu H., Lei Xu , and Bao Z(2011), Radar HRRP Statistical Recognition With Local Factor Analysis by Automatic Bayesian Ying-Yang Harmony Learning, IEEE Trans. Signal Process., 2011, 59(2):610–617.
  • Zhi-Yong Liu, Hong Qiao, and Lei Xu, (2006), `` Multisets mixture learning-based ellipse detection ", Pattern Recognition 39, pp731-735, 2006.
  • Zhi-Yong Liu, Kai-Chun Chiu, and Lei Xu, (2003), `` Strip Line Detection and Thinning by RPCL-Based Local PCA", Pattern Recognition Letters 24, pp2335¨C2344, 2003.
  • Zhi-Yong Liu, Kai-Chun Chiu, and Lei Xu, (2003), " Improved system for object detection and star/galaxy classification via local subspace analysis ", Neural Networks, Vol. 16, pp437¨C451, 2003.
  • Zhi-Yong Liu and Lei Xu, (2003) ``Topological Local Principal Component Analysis", Neurocomputing, Vol. 55, No. 3-4, pp. 739-745, 2003.
  • Yiu-ming Cheung and Lei Xu (2000), ``A RPCL-based Approach for Markov Model Identification with Unknown State Number'', IEEE Signal Processing Letters, Vol. 7, No.10, 284-287 (2000).
  • Yiu-ming Cheung and Lei Xu (2000), ``Rival Penalized Competitive Learning Based Approach for Discrete-valued Source Separation'', International Journal of Neural Systems, Vol.10, No.6, pp483-490, 2000.
  • John Sum, C. Leung, Lai-wan Chan and Lei Xu (1997), ``Yet Another Algorithm Which Can Generate Topography Map", IEEE Trans. on Neural Networks, Vol.5, No.5, pp1204-1207, 1997.

Gaussian Mixture and EM Algorithm

  • Lei Xu, (2003), ``Data smoothing regularization, multi-sets-learning, and problem solving strategies", Neural Networks, Vol. 16, pp817¨C825, 2003..
  • Lei Xu (2002), ``BYY harmony learning, structural RPCL, and topological self-organizing on mixture models", Neural Networks, Vol. 15, pp1125-1151, 2002.
  • 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 (1997), ``Bayesian Ying-Yang Machine, Clustering and Number of Clusters", Pattern Recognition Letters, Vol.18, No.11-13, pp1167-1178, 1997.
  • Lei Xu & M.I.Jordan (1996), ``On convergence properties of the em algorithm for gaussian mixtures", Neural Computation, No.1, Jan, 1996, pp129-151.
  • Lei Xu (1997), ``Comparative Analysis on Convergence Rate of The EM Algorithm and Its Two Modifications for Gaussian Mixtures", Neural Processing Letters 6, pp69-76, 1997.
  • J. Ma, Lei Xu and M.I.Jordan (2000), `` Asymptotic Convergence Rate of the EM Algorithm for Gaussian Mixtures ", Neural Computation, Vol.12, No.12, pp2881-2908, 2000.
  • J. Ma and Lei Xu (2005), ``Asymptotic convergence properties of the EM algorithm with respect to the overlap in the mixture", Neurocomputing, Vol 68, pp105 - 129, 2005.

Bayesian Approach

  • Lei Xu (1996), ``A Maximum Balanced Mapping Certainty Principle for Pattern Recognition and Associative Mapping", Proc. of 1996 World Congress on Neural Networks, Sept. 15-18, 1996, SanDiego, CA, pp.946-949.
  • Lei Xu & J.Pearl, (1989), `` Structuring Casual Tree Models with Continuous Variables", in Uncertainty in Artificial Intelligence 3, L.N.Kanal et al ed., Elsevier Science Publishers B.V. (North-Holland), 1989 pp209-219.
  • Alan Yuille, Stelios Smirnakis & Lei Xu (1995), ``Bayesian Self-Organization for visual processing'', Neural Computation 7, pp580-593.