mcr2

This paper proposes LA-ReduNet, a lightweight adaptive architecture that uses hyperspherical manifold learning and adaptive step sizes to significantly reduce the number of layers needed for the MCR2 objective in neural networks, achieving comparable classification accuracy with far fewer parameters.