ICANN ’94 pp 479-486 | Cite as

Hierarchical Mixtures of Experts and the EM Algorithm

  • M. I. Jordan
  • R. A. Jacobs
Conference paper


In the statistical literature and in the machine learning literature, divide-and-conquer algorithms have become increasingly popular. The CART algorithm (Breiman, et al., 1984) and the MARS algorithm (Friedman, 1991) are well-known examples. These algorithms fit surfaces to data by explicitly dividing the input space into a nested sequence of regions, and by fitting simple surfaces (e.g., constant functions) within these regions. The advantages of these algorithms include the interpretability of their solutions and the speed of the training process.


Dispersion Parameter Multivariate Adaptive Regression Spline Nest Sequence Expert Network Multinomial Probability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London Limited 1994

Authors and Affiliations

  • M. I. Jordan
    • 1
  • R. A. Jacobs
    • 2
  1. 1.Massachusetts Institute of TechnologyCambridgeUSA
  2. 2.University of RochesterRochesterUSA

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