2023
Robust low-rank training via approximate orthonormal constraints
NeurIPS 2023poster
With the growth of model and data sizes, a broad effort has been made to design pruning techniques that reduce the resource demand of deep learning pipelines, while retaining model performance. In order to reduce both inference and training costs, a prominent line of work uses low-rank matrix factor…