Mixtures and Hierarchical Mixtures of Experts


Background ----- Mixtures and hierarchical mixtures of experts (ME and HME)  are generalizations of the standard mixture models to the regression context, which combine simple models to form more powerful mixtures. Some pioneering works are done by M. Jordan, R. Jacobs, G. Hinton, M. TannerA. Zeevi, and S. Waterhouse who provides a bibliography and computing software.

See an online document for an overview of theoretical developments of ME and HME:
Mixtures and Hiearchical Mixtures of Experts: A Theoretical Overview. (Html)
 
Technical Reports
(A sequence of papers on the theory of mixtures-of-experts: on approximation; frequentists' and Bayesian consistency; asymptotic normality; identifiability; VC dimension)
 
  • On the Approximation Rate of Hierarchical Mixtures-of-Experts for Generalized Linear Models. (with Tanner, M. A.) PostScript Neural Computation 1999

  • Hierarchical Mixtures-of-Experts for Exponential Family Regression Models: Approximation and Maximum Likelihood Estimation. (with Tanner, M. A.) PostScript Annals of Statistics 1999
     
  • On the Asymptotic Normality of Hierarchical Mixtures-of-Experts for Generalized Linear Models. (with Tanner, M. A.) PostScript IEEE Trans. Information Theory 2000
     
  • On the Identifiability of Mixtures-of-Experts. (with Tanner, M. A.) PostScript Neural Networks 1999
     
  • The VC Dimension for Mixtures of Binary Classifiers. PostScript Neural Computation 2000
     
  • Hierarchical Mixtures-of-Experts for Generalized Linear Models: Some Results on Denseness and consistency. (with Tanner, M.A.; a short survey paper) PostScript Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999. Morgan Kaufmann.

  • On Consistency of Bayesian Inference with Mixtures of Logistic Regression. (with Ge, Y.) Pdf (To appear in Neural Computation, 2006.)
     
  • Regression Analysis of Mean Lifetime: Exploring Nonlinear Relationship with Heteroscedasticity. (with Sun, Z.) The International Journal of Biostatistics: Vol. 3 : Iss. 1, Article 5. (2007). Available at: http://www.bepress.com/ijb/vol3/iss1/5  



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    (last updated on 5/20/2005.)