Learning and Invariance in a Family of Hierarchical Kernels
暂无分享,去创建一个
[1] N. Aronszajn. Theory of Reproducing Kernels. , 1950 .
[2] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[3] Bernhard Schölkopf,et al. Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.
[4] Terrence J. Sejnowski,et al. Slow Feature Analysis: Unsupervised Learning of Invariances , 2002, Neural Computation.
[5] Tai Sing Lee,et al. Hierarchical Bayesian inference in the visual cortex. , 2003, Journal of the Optical Society of America. A, Optics, image science, and vision.
[6] Heiko Wersing,et al. Learning Optimized Features for Hierarchical Models of Invariant Object Recognition , 2003, Neural Computation.
[7] Kunihiko Fukushima,et al. Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position , 1980, Biological Cybernetics.
[8] Tomer Hertz,et al. Learning a Mahalanobis Metric from Equivalence Constraints , 2005, J. Mach. Learn. Res..
[9] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[10] Pietro Perona,et al. One-shot learning of object categories , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[11] Thomas Serre,et al. A feedforward architecture accounts for rapid categorization , 2007, Proceedings of the National Academy of Sciences.
[12] Thomas Serre,et al. Robust Object Recognition with Cortex-Like Mechanisms , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[13] Tomaso Poggio,et al. Trade-Off between Object Selectivity and Tolerance in Monkey Inferotemporal Cortex , 2007, The Journal of Neuroscience.
[14] Geoffrey E. Hinton. Reducing the Dimensionality of Data with Neural , 2008 .
[15] Honglak Lee,et al. Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations , 2009, ICML '09.
[16] Yann LeCun,et al. What is the best multi-stage architecture for object recognition? , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[17] Quoc V. Le,et al. Measuring Invariances in Deep Networks , 2009, NIPS.
[18] Lorenzo Rosasco,et al. Publisher Accessed Terms of Use Detailed Terms Mathematics of the Neural Response , 2022 .
[19] Hossein Mobahi,et al. Deep Learning via Semi-supervised Embedding , 2012, Neural Networks: Tricks of the Trade.
[20] Priati,et al. Probabilistic Grammars and Their Applications , .