Modeling image patches with a directed hierarchy of Markov random fields

Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference

Volumn , Issue , 2008, Pages

  Osindero, Simon ^a   Hinton, Geoffrey ^a  

^a UNIVERSITY OF TORONTO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE SEGMENTATION;

EFFICIENT LEARNING; FAST INFERENCE; GENERATIVE MODEL; HIDDEN LAYERS; IMAGE PATCHES; LEARNING PROCEDURES; MARKOV RANDOM FIELDS; MODEL IMAGES; POSTERIOR DISTRIBUTIONS; TOPDOWN;

MARKOV PROCESSES;

EID: 85161976678     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. Bell, A. J. and Sejnowski, T. J. (1997). The "independent components" of natural scenes are edge filters. Vision Research, 37(23):3327-3338. (Pubitemid 27493806)
2. Bengio, Y., Lamblin, P., Popovici, D., and Larochelle, H. (2007). Greedy layer-wise training of deep networks. In B., S., Platt, J., and Hoffman, T., editors, Advances in Neural Information Processing Systems 19. MIT Press, Cambridge, MA.
3. Geman, S. and Geman, D. (1984). Stochastic relaxation, gibbs distributions and the bayesian restoration of images. IEEE Trans. Pattern Anal. Mach. Intell, 6.
4. Hinton, G. E. (2002). Training products of experts by minimizing contrastive divergence. Neural Computation, 14(8):1711-1800.
5. Hinton, G. E., Osindero, S., and Teh, Y. W. (2006). A fast learning algorithm for deep belief nets. Neural Computation, 18.
6. Hinton, G. E. and Salakhutdinov, R. (2006). Reducing the dimensionality of data with neural networks. Science, 313.
7. Karklin, Y. and Lewicki, M. (2005). A hierarchical bayesian model for learning nonlinear statistical regularities in nonstationary natural signals. Neural Computation, 17(2).
8. Lyu, S. and Simoncelli, E. (2006). Statistical modeling of images with fields of gaussian scale mixtures. In Advances Neural Information Processing Systems, volume 19.
9. Memisevic, R. F. and Hinton, G. E. (2007). Unsupervised learning of image transformations. In Computer Vision and Pattern Recognition. IEEE Computer Society.
10. Olshausen, B. A. and Field, D. J. (1996). Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381(6583):607-609. JUN 13 NATURE. (Pubitemid 26177476)
11. Osindero, S.,Welling, M., and Hinton, G. E. (2006). Topographic product models applied to natural scene statistics. Neural Computation, 18(2).
12. Taylor, G. W., Hinton, G. E., and Roweis, S. (2007). Modeling human motion using binary latent variables. In B., S., Platt, J., and Hoffman, T., editors, Advances in Neural Information Processing Systems 19. MIT Press, Cambridge, MA.
13. Wainwright, M. and Simoncelli, E. (2000). Scale mixtures of Gaussians and the statistics of natural images. In Advances Neural Information Processing Systems, volume 12, pages 855-861.
14. Welling,M. and Hinton, G. E. (2002). A new learning algorithm for mean field boltzmann machines. In International Joint Conference on Neural Networks, Madrid.