Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics
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[1] L. Younes. Parametric Inference for imperfectly observed Gibbsian fields , 1989 .
[2] Heekuck Oh,et al. Neural Networks for Pattern Recognition , 1993, Adv. Comput..
[3] C. Geyer. On the Convergence of Monte Carlo Maximum Likelihood Calculations , 1994 .
[4] Christopher M. Bishop,et al. Neural networks for pattern recognition , 1995 .
[5] David J. Field,et al. Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.
[6] J. V. van Hateren,et al. Independent component filters of natural images compared with simple cells in primary visual cortex , 1998, Proceedings of the Royal Society of London. Series B: Biological Sciences.
[7] J. H. Hateren,et al. Independent component filters of natural images compared with simple cells in primary visual cortex , 1998 .
[8] Hoon Kim,et al. Monte Carlo Statistical Methods , 2000, Technometrics.
[9] S. Nash. A survey of truncated-Newton methods , 2000 .
[10] Aapo Hyvärinen,et al. Topographic Independent Component Analysis , 2001, Neural Computation.
[11] Geoffrey E. Hinton. Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.
[12] Nicol N. Schraudolph,et al. Towards stochastic conjugate gradient methods , 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..
[13] Yee Whye Teh,et al. Energy-Based Models for Sparse Overcomplete Representations , 2003, J. Mach. Learn. Res..
[14] Eric R. Ziegel,et al. The Elements of Statistical Learning , 2003, Technometrics.
[15] Larry Wasserman,et al. All of Statistics , 2004 .
[16] Eero P. Simoncelli,et al. Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.
[17] Yuhong Yang,et al. Information Theory, Inference, and Learning Algorithms , 2005 .
[18] Christian P. Robert,et al. Monte Carlo Statistical Methods (Springer Texts in Statistics) , 2005 .
[19] Michael S. Lewicki,et al. A Hierarchical Bayesian Model for Learning Nonlinear Statistical Regularities in Nonstationary Natural Signals , 2005, Neural Computation.
[20] Aapo Hyvärinen,et al. Estimation of Non-Normalized Statistical Models by Score Matching , 2005, J. Mach. Learn. Res..
[21] Geoffrey E. Hinton,et al. Topographic Product Models Applied to Natural Scene Statistics , 2006, Neural Computation.
[22] Geoffrey E. Hinton,et al. Modeling image patches with a directed hierarchy of Markov random fields , 2007, NIPS.
[23] Jörg Lücke,et al. Maximal Causes for Non-linear Component Extraction , 2008, J. Mach. Learn. Res..
[24] Tijmen Tieleman,et al. Training restricted Boltzmann machines using approximations to the likelihood gradient , 2008, ICML '08.
[25] Aapo Hyvärinen,et al. Optimal Approximation of Signal Priors , 2008, Neural Computation.
[26] Aapo Hyvärinen,et al. Learning Features by Contrasting Natural Images with Noise , 2009, ICANN.
[27] Aapo Hyvärinen,et al. A Two-Layer Model of Natural Stimuli Estimated with Score Matching , 2010, Neural Computation.
[28] James Martens,et al. Deep learning via Hessian-free optimization , 2010, ICML.
[29] Ya-Xiang Yuan,et al. Optimization Theory and Methods: Nonlinear Programming , 2010 .
[30] Aapo Hyvärinen,et al. A Family of Computationally E cient and Simple Estimators for Unnormalized Statistical Models , 2010, UAI.
[31] Geoffrey E. Hinton,et al. Modeling pixel means and covariances using factorized third-order boltzmann machines , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[32] Aapo Hyvärinen,et al. Noise-contrastive estimation: A new estimation principle for unnormalized statistical models , 2010, AISTATS.
[33] Andrew Gelman,et al. Handbook of Markov Chain Monte Carlo , 2011 .
[34] Seungjin Choi,et al. Independent Component Analysis , 2009, Handbook of Natural Computing.
[35] Linda C. van der Gaag,et al. Probabilistic Graphical Models , 2014, Lecture Notes in Computer Science.