Task: Language Identification
Input (Spanish, English): Summary of the paper  The paper studies the invertiblity of convolutional neural network in the random model. A reconstruction algorithm similar to IHT is proposed for layer-wise inversion of the network.    Clarity:  - The paper is confusing wrt to standard notations in deep learning.  Comments:  The paper makes two simplifications in the analysis of a CNN, that makes it map to a model based compressive sensing framework:  1-  The non linearity (RELU) is dropped. This is a big simplification, for random gaussian weights for instance we know by JL that we can preserve L_2 distance, when RELU is applied the metric changes (see for instance the kernel for n=1 in
Output (English): en