A Neural Network model with Bidirectional Whitening

Yuki Fujimoto; Toru Ohira

doi:10.1007/978-3-319-91253-0_5

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arXiv · 1704.07147

A Neural Network model with Bidirectional Whitening

Yuki Fujimoto·Toru Ohira

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Abstract

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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BibTeX RIS

Yuki Fujimoto, Toru Ohira. 2017-04-24. A Neural Network model with Bidirectional Whitening. https://doi.org/10.1007/978-3-319-91253-0_5

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