Learning Causally Linked Markov Random Fields
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[1] N. Wermuth,et al. Graphical Models for Associations between Variables, some of which are Qualitative and some Quantitative , 1989 .
[2] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[3] Wray L. Buntine. Chain graphs for learning , 1995, UAI.
[4] Geoffrey E. Hinton,et al. The "wake-sleep" algorithm for unsupervised neural networks. , 1995, Science.
[5] J. Cardoso. Infomax and maximum likelihood for blind source separation , 1997, IEEE Signal Processing Letters.
[6] Geoffrey E. Hinton,et al. A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants , 1998, Learning in Graphical Models.
[7] Pietro Perona,et al. Unsupervised Learning of Models for Recognition , 2000, ECCV.
[8] H. Sebastian Seung,et al. Algorithms for Non-negative Matrix Factorization , 2000, NIPS.
[9] Yee Whye Teh,et al. Rate-coded Restricted Boltzmann Machines for Face Recognition , 2000, NIPS.
[10] Geoffrey E. Hinton. Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.
[11] S. Lauritzen,et al. Chain graph models and their causal interpretations , 2002 .
[12] Geoffrey E. Hinton,et al. A New Learning Algorithm for Mean Field Boltzmann Machines , 2002, ICANN.