Data-Free Knowledge Amalgamation via Group-Stack Dual-GAN
Data-Free Knowledge Amalgamation via Group-Stack Dual-GAN
Recent advances in deep learning have provided procedures for learning one network to amalgamate multiple streams of knowledge from the pre-trained Convolutional Neural Network (CNN) models, thus reduce the annotation cost. However, almost all existing methods demand massive training data, which may be unavailable due to privacy or transmission issues. …