Convergence results for the EM approach to mixtures of experts architectures
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Michael I. Jordan | Lei Xu | Lei Xu | L. Xu
[1] Michael I. Jordan,et al. On Convergence Properties of the EM Algorithm for Gaussian Mixtures , 1996, Neural Computation.
[2] Robert A. Jacobs,et al. Hierarchical Mixtures of Experts and the EM Algorithm , 1993, Neural Computation.
[3] Michael I. Jordan,et al. Hierarchies of Adaptive Experts , 1991, NIPS.
[4] J. Friedman. Multivariate adaptive regression splines , 1990 .
[5] Geoffrey E. Hinton,et al. Adaptive Mixtures of Local Experts , 1991, Neural Computation.
[6] I. Meilijson. A fast improvement to the EM algorithm on its own terms , 1989 .
[7] D. N. Geary. Mixture Models: Inference and Applications to Clustering , 1989 .
[8] D. Rubin,et al. Statistical Analysis with Missing Data. , 1989 .
[9] R. D. Veaux. Parameter estimation for a mixture of linear regressions (em algorithm, asymptotic efficiency) , 1986 .
[10] R. Redner,et al. Mixture densities, maximum likelihood, and the EM algorithm , 1984 .
[11] New York Dover,et al. ON THE CONVERGENCE PROPERTIES OF THE EM ALGORITHM , 1983 .
[12] J. B. Ramsey,et al. Estimating Mixtures of Normal Distributions and Switching Regressions , 1978 .
[13] H. Walker,et al. THE NUMERICAL EVALUATION OF THE MAXIMUM-LIKELIHOOD ESTIMATE OF A SUBSET OF MIXTURE PROPORTIONS* , 1978 .
[14] H. Walker,et al. An iterative procedure for obtaining maximum-likelihood estimates of the parameters for a mixture of normal distributions , 1978 .
[15] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[16] R. Quandt. A New Approach to Estimating Switching Regressions , 1972 .
[17] L. Baum,et al. A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains , 1970 .
[18] L. Baum,et al. Growth transformations for functions on manifolds. , 1968 .
[19] W. Loh,et al. Classification and regression trees , 2022 .