Deep Boltzmann Machines
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[1] Tamio Shimizu,et al. A Stochastic Approximation Method for Optimization Problems , 1969, Journal of the ACM.
[2] Geoffrey E. Hinton,et al. OPTIMAL PERCEPTUAL INFERENCE , 1983 .
[3] Paul Smolensky,et al. Information processing in dynamical systems: foundations of harmony theory , 1986 .
[4] L. Younes. Parametric Inference for imperfectly observed Gibbsian fields , 1989 .
[5] Radford M. Neal. Connectionist Learning of Belief Networks , 1992, Artif. Intell..
[6] Geoffrey E. Hinton,et al. Autoencoders, Minimum Description Length and Helmholtz Free Energy , 1993, NIPS.
[7] Geoffrey E. Hinton,et al. A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants , 1998, Learning in Graphical Models.
[8] L. Younes. On the convergence of markovian stochastic algorithms with rapidly decreasing ergodicity rates , 1999 .
[9] Radford M. Neal. Annealed importance sampling , 1998, Stat. Comput..
[10] Geoffrey E. Hinton. Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.
[11] Geoffrey E. Hinton,et al. A New Learning Algorithm for Mean Field Boltzmann Machines , 2002, ICANN.
[12] Geoffrey E. Hinton,et al. Exponential Family Harmoniums with an Application to Information Retrieval , 2004, NIPS.
[13] Alan L. Yuille,et al. The Convergence of Contrastive Divergences , 2004, NIPS.
[14] Bernhard Schölkopf,et al. Training Invariant Support Vector Machines , 2002, Machine Learning.
[15] Y. LeCun,et al. Learning methods for generic object recognition with invariance to pose and lighting , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[16] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[17] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[18] H. Robbins. A Stochastic Approximation Method , 1951 .
[19] Yoshua Bengio,et al. Scaling learning algorithms towards AI , 2007 .
[20] Ruslan Salakhutdinov,et al. On the quantitative analysis of deep belief networks , 2008, ICML '08.
[21] Geoffrey E. Hinton,et al. Implicit Mixtures of Restricted Boltzmann Machines , 2008, NIPS.
[22] Tijmen Tieleman,et al. Training restricted Boltzmann machines using approximations to the likelihood gradient , 2008, ICML '08.
[23] R. Salakhutdinov. Learning and Evaluating Boltzmann Machines , 2008 .