The goal of this project is to reproduce the methods and experiments of
the following paper:
C. Cortes, X. Gonzalvo, V. Kuznetsov, M. Mohri, S. Yang AdaNet:
Adaptive Structural Learning of Artificial Neural
Networks. We will try to
reproduce their method that consists in building neural networks whose
structure is learned and optimized at the same time as it’s weights.This
method will be applied to a binary classification task on images from
the CIFAR-10 dataset.