Modular learning of convolutional neural networks - Wang, Jinhua (Nanyang Technological University, 2023)
In recent years, a wide variety of network structures and training methods have been proposed for deep learning. However, the underlying mechanism of a deep network is not fully understood, which is considered as a black box system. The layer-wise learning method was proposed a decade ago, but now it is rarely used due to the trade-off in performance as compared to the standard end-to-end learning. Recently, layer-wise learning has been considered for application in interpretable or analytical neural networks. Therefore, a key target is to improve the performance of the layer-wise learning.