no code implementations • 30 Sep 2022 • Nanyang Ye, Jingbiao Mei, Zhicheng Fang, Yuwen Zhang, Ziqing Zhang, Huaying Wu, Xiaoyao Liang
For neural architecture search space design, instead of conducting neural architecture search on the whole feasible neural architecture search space, we first systematically explore the weight drifting tolerance of different neural network components, such as dropout, normalization, number of layers, and activation functions in which dropout is found to be able to improve the neural network robustness to weight drifting.