Supplement: Discrete Deep Feature Extraction: A Theory and New Architectures
نویسندگان
چکیده
For the handwritten digit classification experiment described in Section 6.1, Table 1 shows the classification error for Daubechies wavelets with 2 vanishing moments (DB2). Table 1. Classification errors in percent for handwritten digit classification using DB2 wavelet filters, different non-linearities, and different pooling operators For the feature importance experiment described in Section 6.2, Figure 1 shows the cumulative feature importance (per triplet of layer index, wavelet scale, and direction, averaged over all trees in the respective RF) in facial landmark detection (right eye and mouth). We verify the Lipschitz property
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Discrete Deep Feature Extraction: A Theory and New Architectures
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