2019
RePr: Improved Training of Convolutional Filters
CVPR 2019oral
A well-trained Convolutional Neural Network can easily be pruned without significant loss of performance. This is because of unnecessary overlap in the features captured by the network's filters. Innovations in network architecture such as skip/dense connections and inception units have mitigated th…