2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.CV2021★ 2 cited
Pi-NAS: Improving Neural Architecture Search by Reducing Supernet Training Consistency Shift
Jiefeng Peng, Jiqi Zhang, Changlin Li +3
Recently proposed neural architecture search (NAS) methods co-train billions of architectures in a supernet and estimate their potential accuracy using the network weights detached…
cs.CV2021
Joint Learning of Neural Transfer and Architecture Adaptation for Image Recognition
Guangrun Wang, Liang Lin, Rongcong Chen +2
Current state-of-the-art visual recognition systems usually rely on the following pipeline: (a) pretraining a neural network on a large-scale dataset (e.g., ImageNet) and (b) finet…