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Invited Talks Classification with Stable Invariants 8:40am Stephane Mallat, Joan Bruna IHES, Ecole Polytechnique, Paris Classification often requires to reduce variability with invariant representations, which are stable to deformations, and retain enough information for discrimination. Deep convolution networks provide architectures to construct such representations. With adapted wavelet filters and a modulus pooling non-linearity, a deep…



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Contributions

https://deeplearningworkshopnips2011.wordpress.com/contributions

Invited Talks Classification with Stable Invariants 8:40am Stephane Mallat, Joan Bruna IHES, Ecole Polytechnique, Paris Classification often requires to reduce variability with invariant representations, which are stable to deformations, and retain enough information for discrimination. Deep convolution networks provide architectures to construct such representations. With adapted wavelet filters and a modulus pooling non-linearity, a deep…



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https://deeplearningworkshopnips2011.wordpress.com/contributions

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Invited Talks Classification with Stable Invariants 8:40am Stephane Mallat, Joan Bruna IHES, Ecole Polytechnique, Paris Classification often requires to reduce variability with invariant representations, which are stable to deformations, and retain enough information for discrimination. Deep convolution networks provide architectures to construct such representations. With adapted wavelet filters and a modulus pooling non-linearity, a deep…

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