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A Neural Network model with Bidirectional Whitening

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 نشر من قبل Yuki Fujimoto
 تاريخ النشر 2017
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We present here a new model and algorithm which performs an efficient Natural gradient descent for Multilayer Perceptrons. Natural gradient descent was originally proposed from a point of view of information geometry, and it performs the steepest descent updates on manifolds in a Riemannian space. In particular, we extend an approach taken by the Whitened neural networks model. We make the whitening process not only in feed-forward direction as in the original model, but also in the back-propagation phase. Its efficacy is shown by an application of this Bidirectional whitened neural networks model to a handwritten character recognition data (MNIST data).



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