Exercise:Sparse Autoencoder
From Ufldl
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In this problem set, you will implement the sparse autoencoder | In this problem set, you will implement the sparse autoencoder | ||
algorithm, and show how it discovers that edges are a good | algorithm, and show how it discovers that edges are a good | ||
- | representation for natural images. | + | representation for natural images. (Images provided by |
- | Bruno Olshausen. | + | Bruno Olshausen.) The sparse autoencoder algorithm is described in |
the lecture notes found on the course website. | the lecture notes found on the course website. | ||
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an 8×8 image patch from the selected image, and convert the image patch (either | an 8×8 image patch from the selected image, and convert the image patch (either | ||
in row-major order or column-major order; it doesn't matter) into a 64-dimensional | in row-major order or column-major order; it doesn't matter) into a 64-dimensional | ||
- | vector to get a training example <math>x \in \Re^{64} | + | vector to get a training example <math>x \in \Re^{64}`.</math> |
Complete the code in <tt>sampleIMAGES.m</tt>. Your code should sample 10000 image | Complete the code in <tt>sampleIMAGES.m</tt>. Your code should sample 10000 image |