A Hierarchical Community of Experts
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[1] Dorothy T. Thayer,et al. EM algorithms for ML factor analysis , 1982 .
[2] Brian Everitt,et al. An Introduction to Latent Variable Models , 1984 .
[3] Geoffrey E. Hinton,et al. Adaptive Mixtures of Local Experts , 1991, Neural Computation.
[4] Radford M. Neal. Connectionist Learning of Belief Networks , 1992, Artif. Intell..
[5] Radford M. Neal. A new view of the EM algorithm that justifies incremental and other variants , 1993 .
[6] Robert A. Jacobs,et al. Hierarchical Mixtures of Experts and the EM Algorithm , 1993, Neural Computation.
[7] Jonathan J. Hull. A Database for Handwritten Text Recognition Research Some of the criticisms of experimental pattern recognition that are related to the replication of experiments and the comparison , 1994 .
[8] Jonathan J. Hull,et al. A Database for Handwritten Text Recognition Research , 1994, IEEE Trans. Pattern Anal. Mach. Intell..
[9] Michael I. Jordan,et al. Hierarchical Mixtures of Experts and the EM Algorithm , 1994, Neural Computation.
[10] Michael I. Jordan,et al. Hierarchical Mixtures of Experts and the EM Algorithm , 1994 .
[11] Geoffrey E. Hinton,et al. The "wake-sleep" algorithm for unsupervised neural networks. , 1995, Science.
[12] Geoffrey E. Hinton,et al. The EM algorithm for mixtures of factor analyzers , 1996 .
[13] Michael I. Jordan,et al. Mean Field Theory for Sigmoid Belief Networks , 1996, J. Artif. Intell. Res..
[14] Geoffrey E. Hinton,et al. Modeling the manifolds of images of handwritten digits , 1997, IEEE Trans. Neural Networks.
[15] Geoffrey E. Hinton,et al. Generative models for discovering sparse distributed representations. , 1997, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[16] Geoffrey E. Hinton,et al. A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants , 1998, Learning in Graphical Models.
[17] Zoubin Ghahramani,et al. A Unifying Review of Linear Gaussian Models , 1999, Neural Computation.