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Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations (2009)

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by Honglak Lee , Roger Grosse , Rajesh Ranganath , Andrew Y. Ng
Venue:IN ICML’09
Citations:369 - 19 self
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Citations

1920 Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories - Lazebnik, Schmid, et al.
1303 Emergence of simple-cell receptive field properties by learning a sparse code for natural images - Olshausen, Field - 1996
970 A fast learning algorithm for deep belief nets,” Neural computation - Hinton, Osindero, et al. - 2006
850 Training products of experts by minimizing contrastive divergence - Hinton
796 Reducing the dimensionality of data with neural networks - Hinton, Salakhutdinov
783 P (2004) Learning generative visual models from few training examples: an incremental Bayesian approach tested on 101 object categories. Paper presented at - Fei-Fei, Fergus, et al.
617 The “independent components” of natural scenes are edge filters - Bell, Sejnowski - 1997
474 Backpropagation applied to handwritten zip code recognition - LeCun, Boser - 1989
419 Shape matching and object recognition using low distortion correspondences - Berg, Berg, et al. - 2005
394 Greedy layer-wise training of deep networks,” - Bengio, Lamblin, et al. - 2007
299 D (2003) Hierarchical bayesian inference in the visual cortex - TS, Mumford
297 Self-taught learning: transfer learning from unlabeled data - Raina, Battle, et al. - 2007
227 Learning the discriminative powerinvariance trade-off. - Varma, Ray - 2007
218 Efficient learning of sparse representations with an energybased model - Ranzato, Poultney, et al. - 2007
194 Multiclass object recognition with sparse, localized features - Mutch, Lowe - 2006
194 Unsupervised learning of invariant feature hierarchies with applications to object recognition - Ranzato, Huang, et al. - 2007
151 Modeling human motion using binary latent variables. - Taylor, Hinton, et al. - 2007
67 Deep learning via semi-supervised embedding. - Weston, Ratle, et al. - 2008
57 Shift-Invariant Sparse Coding for Audio Classification,” - Grosse, Raina, et al. - 2007
54 Representation of angles embedded within contour stimuli in area V2 of macaque monkeys - Ito, Komatsu - 2004
51 Large-scale Deep Unsupervised Learning using Graphics Processors,” - Raina, Madhavan, et al. - 2009
11 Deep learning with kernel regularization for visual recognition. Adv. Neural Information Processing Systems - Yu, Xu, et al. - 2009
9 Sparse deep belief network model for visual area V2 - Lee, Ekanadham, et al. - 2008
1 Empirical evaluation of convolutional RBMs for vision (Technical Report - Desjardins, Bengio - 2008
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