Learning the Architecture of Sum-Product Networks Using Clustering on Variables
暂无分享,去创建一个
[1] Adnan Darwiche,et al. A differential approach to inference in Bayesian networks , 2000, JACM.
[2] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[3] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[4] Nir Friedman,et al. Probabilistic Graphical Models - Principles and Techniques , 2009 .
[5] Ryan P. Adams,et al. Learning the Structure of Deep Sparse Graphical Models , 2009, AISTATS.
[6] Nevin Lianwen Zhang,et al. Hierarchical latent class models for cluster analysis , 2002, J. Mach. Learn. Res..
[7] Pietro Perona,et al. Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.
[8] Yoshua Bengio,et al. Shallow vs. Deep Sum-Product Networks , 2011, NIPS.
[9] Pedro M. Domingos,et al. Sum-product networks: A new deep architecture , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).
[10] Andy Harter,et al. Parameterisation of a stochastic model for human face identification , 1994, Proceedings of 1994 IEEE Workshop on Applications of Computer Vision.