Representative Publications

2009

  • 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 (2009), "Machine learning problems from optimization perspective", A special issue for CDGO 07, Journal of Global Optimization, in press, DOI10.1007/s10898-008-9364-0.

2008

  • 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  and E..Oja (2008),  “Randomized Hough Transform”  in Encyclopedia of Artificial Intelligence,  Edited By: Juan Ramón,  Rabuñal Dopico; Julian Dorado; Alejandro Pazos,  IGI Global (IGI)  publishing company,  pp1354-1361.

·        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 (2008), `` Bayesian Ying Yang System, Best Harmony Learning, and Gaussian Manifold Based Family", In J.M. Zurada et al. (Eds.) Computational Intelligence: Research Frontiers, WCCI2008 Plenary/Invited Lectures, LNCS5050,  48–78, 2008.

2007

·         Lei Xu (2007), Bayesian Ying Yang Learning,  In Scholarpedia, no.18395, http://scholarpedia.org, 2007.

  • 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 (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 (2007), `` One-Bit-Matching Theorem for ICA, Convex-Concave Programming on Polyhedral Set, and Distribution Approximation for Combinatorics ",  Neural Computation, 19: 546-569. 2007 .

 

2006

 

·         An, Y.J., Hu, X.L.,  and Lei Xu (2006), ``A Comparative Investigation on Model Selection in Independent Factor Analysis" Journal of Mathematical Modeling and Algorithms 5,   pp.447–473.

  • Zhi-Yong Liu, Hong Qiao, and Lei Xu, (2006), `` Multisets mixture learning-based ellipse detection ", Pattern Recognition 39, pp731-735, 2006.

 

2005

  • Lei Xu (2005), ``Fundamentals, Challenges, and Advances of Statistical Learning for Knowledge Discovery and Problem Solving: A BYY Harmony Perspective", Proceedings of International Conference on Neural Networks and Brain, Keynote talk, Vol. 1, pp. 24-55, Oct. 13-15,Beijing, China, 2005.
  • 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.
  • Jinwen Ma , Zhi Yong Liu, and Lei Xu, (2005), `` A Further Result on the ICA One-Bit-Matching Conjecture", Neural Computation, Vol. 17, No. 2, 2005, pp331-334.

2004

  • Lei Xu (2004), ``Temporal BYY Encoding, Markovian State Spaces, and Space Dimension Determination", IEEE Trans on Neural Networks, Vol. 15, No. 5, pp1276-1295, 2004.
  • Lei Xu (2004), ``Advances on BYY Harmony Learning: Information Theoretic Perspective, Generalized Projection Geometry, and Independent Factor Auto-determination", IEEE Trans on Neural Networks, Vol. 15, No. 4, pp885-902, 2004.
  • Lei Xu (2004), ``Bayesian Ying Yang Learning (I): A Unified Perspective for Statistical Modeling", Intelligent Technologies for Information Analysis, N. Zhong and J. Liu (eds), Springer, pp615-659, 2004.
  • Lei Xu (2004), ``Bayesian Ying Yang Learning (II): A New Mechanism for Model Selection and Regularization", Intelligent Technologies for Information Analysis, N. Zhong and J. Liu (eds), Springer, pp661-706, 2004.
  • Kai-Chun Chiu, and Lei Xu (2004), ``Arbitrage Pricing Theory Based Gaussian Temporal Factor Analysis for Adaptive Portfolio Management", Special Issue on Data Mining for Financial Decision Making, The Journal of Decision Support Systems, pp 485- 500, 2004..
  • Kai-Chun Chiu, and Lei Xu (2004), ``NFA for Factor Number Determination in APT", International Journal of Theoretical and Applied Finance, pp 253-267, 2004..
  • X. Hu and Lei Xu (2004), ``A comparative investigation on subspace dimension determination", Neural Networks , Vol. 17, pp1051¨C1059, 2004,
  • X. Hu and Lei Xu (2004), ``Investigation on Several Model Selection Criteria for Determining the Number of Cluster", Neural Information Processing - Letters and Reviews, Vol. 4, No. 1, pp1-10, July 2004,
  • Zhi Yong Liu, Kai Chun Chiu, and Lei Xu, (2004) ``Investigation on Non-Gaussian Factor Analysis", IEEE Signal Processing Letters, Vol. 11, No.7, pp597-600, 2004.
  • Zhi Yong Liu, Kai Chun Chiu, and Lei Xu, (2004) ``One-Bit-Matching Conjecture for Independent Component Analysis", Neural Computation, Vol. 16, No. 2, pp. 383-399.
  • Ma, J, Wang, T, and Lei Xu (2004), ``A gradient BYY harmony learning rule on Gaussian mixture with automated model selection", Neurocomputing, Vol 56, 481 - 487, 2004.

2003

  • Lei Xu, (2003), ``Data smoothing regularization, multi-sets-learning, and problem solving strategies", Neural Networks, Vol. 16, pp817¨C825, 2003..
  • 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.
  • 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 (2003), ``Distribution Approximation, Combinatorial Optimization, and Lagrange-Barrier", Proceedings of International Joint Conference on Neural Networks 2003 (IJCNN '03)}, July 20-24, 2003, Jantzen Beach, Portland, Oregon, pp2354-2359.
  • 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 (2003), `` Further studies on temporal factor analysis: comparison and Kalman Filter-based algorithm ", Neurocomputing, Vol. 50, 2003, 87-103.
  • Yiu-ming Cheung and Lei Xu (2003), `` Dual Multivariate Auto-Regressive Modeling in State Space for Temporal Signal Separation", IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, Volume: 33, No. 3, June 2003, pp386- 398.
  • Kei Keung Hung, Yiu-ming Cheung, and Lei Xu (2003), `` An Extended ASLD Trading System to Enhance Portfolio Management", IEEE Transactions on Neural Networks, Vol. 14, No. 2, 2003, 413-425.
  • Chiu KC and Lei Xu (2003), ``White noise tests and synthesis of APT economic factors using TFA", Computational Intelligence in Economics and Finance,S-H Chen and P Wang (Ed.), Series on Advanced Information Processing (series editor: L. Jain), Springer Verlag, 2003, pp. 405-419.
  • Chiu KC and Lei Xu (2003), ``Optimizing financial portfolios from the perspective of mining temporal structures of stock returns", Lecture Notes in AI, LNAI 2734, Proc. of 2003 Machine Learning and Data Mining in Pattern Recognition, P. Perner and A. Rosenfeld, eds., Springer Verlag, pp266-275.
  • Chiu KC and Lei Xu (2003), ``Stock forecasting by ARCH driven gaussian TFA and alternative mixture experts models", Proc. of 3rd International Workshop on Computational Intelligence in Economics and Finance (CIEF'2003), North Carolina, USA, September 26-30, 2003, pp 1096 -1099.
  • Chiu KC and Lei Xu (2003), ``On generalized arbitrage pricing theory analysis: empirical investigation of the macroeconomics modulated independent state-space model", Proceedings of 2003 International Conference on Computational Intelligence for Financial Engineering (CIFEr2003), Hong Kong, March 20-23, 2003, pp 139-144.
  • Tang, H, Chiu KC, and Lei Xu (2003), ``Finite Mixture of ARMA-GARCH Model For Stock Price Prediction", Proc. of 3rd International Workshop on Computational Intelligence in Economics and Finance (CIEF'2003), North Carolina, USA, September 26-30, 2003, pp.1112-1119.
  • Tang, H and Lei Xu (2003), ``MIXTURE-OF-EXPERT ARMA-GARCH MODELS FOR STOCK PRICE PREDICTION", Proc. of 2003 International Conference on Control, Automation, and Systems (ICCAS 2003), October 22-25, 2003 Gyeongju, KOREA, pp402-407.

2002

  • Lei Xu (2002), `` Ying-Yang learning", The Handbook of Brain Theory and Neural Networks, 2nd ed., Michael A. Arbib, The MIT Press, pp1231-1237, 2002.
  • Lei Xu (2002), ``BYY harmony learning, structural RPCL, and topological self-organizing on mixture models", Neural Networks, Vol. 15, pp1125-1151, 2002.
  • Chiu KC and Lei Xu (2002), ``A comparative study of Gaussian TFA learning and statistical tests for determination of factor number in APT", Proceedings of International Joint Conference on Neural Networks 2002 (IJCNN '02), Honolulu, Hawaii, USA, May 12-17, 2002, pp 2243-2248.
  • Chiu KC and Lei Xu (2002), ``Stock price and index forecasting by arbitrage pricing theory-based gaussian TFA learning", Lecture Notes in Computer Sciences, Vol.2412, in H. Yin et al., eds., Springer Verlag, 2002, pp366-371.
  • Chiu KC and Lei Xu (2002), ``Financial APT-based gaussian TFA learning for adaptive portfolio management", Lecture Notes in Computer Sciences, Vol.2415, in J.R. Dorronsoro (Ed.), Springer Verlag, 2002, pp 1019-1024.

2001

  • Lei Xu (2001), ``BYY Harmony Learning, Independent State Space and Generalized APT Financial Analyses", IEEE Trans. on Neural Networks, Vol. 12, No.4, pp822-849, July, 2001. An Errata to this paper is given on IEEE Trans. on Neural Networks, Vol. 13, No.4, 1023, July, 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 ,(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.
  • Lei Xu and Irwin King, (2001), ``A PCA approach for fast retrieval of structural patterns in attributed graphs", IEEE Transactions on Systems, Man and Cybernetics, Part B, Vol. 31, No. 5 , Oct. 2001, pp 812 -817.
  • Chuangyin Dang and Lei Xu (2001), ``A Lagrange Multiplier and Hopfield-Type Barrier Function Method for the Traveling Salesman Problem", Neural Computation, Vol. 14 , No. 2, pp303 - 324.
  • Chuangyin Dang and Lei Xu (2001), ``A globally convergent Lagrange and barrier function iterative algorithm for the traveling salesman problem", Neural Networks, Vol.14, No.2, pp217-230, 2001.
  • Yiu-ming Cheung and Lei Xu (2001), ``Independent Component Ordering in ICA Time Series Analysis'', Neurocomputing, Vol. 41, No. 1-4, pp145-152, 2001.
  • Chiu KC and Lei Xu (2001), ``Tests of Gaussian Temporal Factor Loadings in Financial APT", Proc. of 3rd International Conference on Independent Component Analysis and Blind Signal Separation, December 9-12, 2001 - San Diego, California, USA, pp313-318.

 

2000

  • Lei Xu (2000), `` Temporal BYY Learning for State Space Approach, Hidden Markov Model and Blind Source Separation ", IEEE Trans on Signal Processing, Vol. 48, No. 7, 2132-2144, July, 2000.
  • Lei Xu (2000), `` BYY Learning System and Theory for Parameter Estimation, Data Smoothing Based Regularization and Model Selection ", Neural, Parallel and Scientific Computations, Vol. 8, pp55-82, 2000.
  • C.C.Cheung and Lei Xu, (2000), `` Some Global and Local Convergence Analysis on The Information-Theoretic Independent Component Analysis Approach ", Neurocomputing, Vol.30, pp79-102, 2000.
  • 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.
  • 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.

 

1999

  • 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.
  • 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.

1998

  • Lei Xu (1998), ``RBF Nets, Mixture Experts, and Bayesian Ying-Yang Learning", Neurocomputing, Vol. 19, No.1-3, pp223-257, 1998.
  • Lei Xu(1998), ``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(1998), ``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 (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 (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.
  • Lei Xu and W.M.Leung (1998) , ``Cointegration by MCA and modular MCA", Proceedings of IEEE/IAFE 1998 International Conference on Computational Intelligence for Financial Engineering (CIFEr), March 29-31, New York City, pp157-160.

1997

  • 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 (1997), ``Comparative Analysis on Convergence Rate of The EM Algorithm and Its Two Modifications for Gaussian Mixtures", Neural Processing Letters 6, pp69-76, 1997.
  • Lei Xu (1997), ``New Advances on Bayesian Ying-Yang Learning System With Kullback and Non-Kullback Separation Functionals", Proceedings of 1997 IEEE-(INNS) Conference on Neural Networks, Houston, TX, June. 9-12, Vol. 3, pp1942-1947, 1997
  • Lei Xu (1997), `` Bayesian Ying-Yang System and Theory as A Unified Statistical Learning Approach (III): Models and Algorithms for Dependence Reduction, Data Dimension Reduction, ICA and Supervised Learning", Invited paper, K.W.Wong, I. King and D.Y.Yeung eds, Theoretical Aspects of Neural Computation: A Multidisciplinary Perspective (TANC97), Springer-Verlag, pp43-60, 1997.
  • Lei Xu (1997), ``Bayesian Ying-Yang System and Theory as A Unified Statistical Learning Approach: (II) From Unsupervised Learning to Supervised Learning and Temporal Modeling ", Invited paper, K.W.Wong, I. King and D.Y.Yeung eds, Theoretical Aspects of Neural Computation: A Multidisciplinary Perspective (TANC97), Springer-Verlag, pp25-42, 1997.
  • Lei Xu (1997), ``Bayesian Ying-Yang System and Theory: An Unified Approach for Statistical Learning: (I) Unsupervised and Semi-Unsupervised Learning", Invited paper, S. Amari and N. Kassabov eds., Brain-like Computing and Intelligent Information Systems, Springer-Verlag, pp241-274, 1997.
  • Lei Xu, C.C. Cheung, H.H. Yang and S.-I. Amari(1997), `` Independent component analysis by the information-theoretic approach with Mixture of Density ", Proc. of 1997 IEEE Intl. Conf on Neural Networks (IEEE-INNS IJCNN97)}, June 9-12, Houston, TX, USA, Vol. III, pp1821-1826(1997).
  • Lei Xu, C.C. Cheung, J. Ruan, and S.-I. Amari(1997), ``Nonlinearity and Separation Capability: Further Justification for the ICA Algorithm with A Learned Mixture of Parametric Densities", Invited special session on Blind Signal Separation, Proc. of 1997 European Symp. on Artificial Neural Networks, Bruges, April 16-18, pp291-296(1997).
  • 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.
  • Leung,W.M, Y. M. Cheung and Lei Xu,(1997), `` Application of mixture of experts models to nonlinear financial forecasting",   Nonlinear Financial Forecasting: Proceedings of the First INFFC, R.B.Caldwell ed, Finance & Technology Publishing, pp153-168, 1997.
  • Lei Xu and Y.M. Cheung (1997), `` Adaptive supervised learning decision networks for trading and portfolio management", Journal of Computational Intelligence in Finance, Nov/Dec issue, pp11-16, Finance \& Technology Publishing, 1997.
  • Yiu-ming Cheung, W.M. Leung, and Lei Xu (1997), ``Adaptive Rival Penalized Competitive Learning and Combined Linear Predictor Model for Financial Forecast and Investment'', International Journal of Neural Systems, Vol.8, No.5&6, 1997.

 

1996

  • 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 (1996),``A Unified Learning Scheme: Bayesian-Kullback YING-YANG Machine", Advances in Neural Information Processing Systems 8, eds., David S. Touretzky, Michael Mozer, Michael Hasselmo, MIT Press, Cambridge MA, 1996, pp444-450.
  • 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.
  • 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.
  • Yiu-ming Cheung, Zhihong Lai and Lei Xu (1996), ``Adaptive Rival Penalized Competitive Learning and Combined Linear Regressions with Application to Finacial Investment", Proceedings of IEEE/IAFE 1997 International Conference on Computational Intelligence for Financial Engineering (CIFEr), march 24-26, New York City, pp141-147.
  • Cheung, Y.M, Leung,W.M, and Lei Xu (1996),``Combination Of Buffered Back-propagation And RPCL-CLP By Mixture-of-Experts Model For Foreign Exchange Rate Forecasting", Neural Networks in Financial Engineering: Proc. of 3rd Intl Conf. on Neural Networks in the Capital Markets, Oct.11-13, London, UK, 1996, World Scientific Pub, pp554-563.
  • 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.

 

1995

  • Lei Xu (1995), `` Bayesian-Kullback Coupled YING-YANG Machines: Unified Learnings and New Results on Vector Quantization", Proceedings of International Conference on Neural Information Processing, Keynote Speaker, Oct 30-Nov.3, Beijing, China, 1995, pp977-988.
  • 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 & 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.
  • H.Kalviainen, P.Hirvonen, Lei Xu, & E.Oja, (1995), ``Probabilistic and Non-probabilistic Hough Transforms: Overview and Comparisons", Image and Vision Computing, Vol.5, No. 4, May, 1995.
  • 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.
  • Alan Yuille, Stelios Smirnakis & Lei Xu (1995), ``Bayesian Self-Organization for visual processing'', Neural Computation 7, pp580-593.
  • 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 (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 (1995)``On The Hybrid LT Combinatorial Optimization: New $U$-Shape Barrier, Sigmoid Activation, Least Leaking Energy and Maximum Entropy", Proc. 1995 Intl Conf. on Neural Information Processing (ICONIP95), Oct 30 - Nov. 3, Beijing, Vol. I, pp309-312.
  • Lei Xu(1995), ``Channel Equalization by Finite Mixtures and The EM Algorithm", Proc. of IEEE Neural Networks and Signal Processing 1995 Workshop, Vol.5, pp603-612, August 31 - September 2, 1995, Cambridge, Massachusetts, USA.
  • S.M. Chan, K.M. Lau and Lei Xu (1995), ``Comparison on the Hopfield scheme and the Hybrid Lagrange and Transformation Approaches for Solving the Traveling Salesman Problem", Proc. of 1995 Intl IEEE Symposium on Intelligence in Neural and Biological Systems, May 29-31,1995, Washington DC, USA, IEEE Computer Society Press, pp209-218.

 

1994

  • 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, 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, 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 (1994)``Combinatorial Optimization Neural Nets Based on A Hybrid of Lagrange and Transformation Approaches", 1994 Proc. of World Congress on Neural Networks, June 4-9, 1994, SanDiego, CA, Vol.II, 399-404,
  • 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.
  • Lei Xu (1994), ``Signal Segmentation by Finite Mixture Model and EM Algorithm", Proceedings of 1994 Intl. Symposium on Artificial Neural Networks, Dec. 15-17, Tainan, Taiwan, pp453-458.

 

1993

  • 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. 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.
  • Lei Xu & E.Oja, (1993), "Randomized Hough Transform (RHT): Basic Mechanisms, Algorithms and Complexities", Computer Vision, Graphics, and Image Processing : Image Understanding, Vol.57, No.2, March, 1993, pp131-154.

1992

  • 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.
  • 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, 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.

 

1991

  • 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.

1990

 

  • 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, E.Oja, & P.Kultanen, (1990), `` A New Curve Detection Method: Randomized Hough Transform (RHT)", Pattern Recognition Letters, Vol.11, pp331-338, 1990.

1989

  • 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.
  • Lei Xu and E.Oja (1989), ``Improved Simulated Annealing, Boltzmann Machine and Attributed Graph Matching", in G.Goos and J.Hartmanis eds., Lecture Notes in Computer Sciences, Vol.412, Springer-Verlag, pp.151-160.