1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.CV2022★ 1 cited
Deep AutoAugment
Yu Zheng, Zhi Zhang, Shen Yan +1
While recent automated data augmentation methods lead to state-of-the-art results, their design spaces and the derived data augmentation strategies still incorporate strong human p…
cs.CV2020
Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?
Shen Yan, Yu Zheng, Wei Ao +2
Existing Neural Architecture Search (NAS) methods either encode neural architectures using discrete encodings that do not scale well, or adopt supervised learning-based methods to…
cs.LG2019
HM-NAS: Efficient Neural Architecture Search via Hierarchical Masking
Shen Yan, Biyi Fang, Faen Zhang +4
The use of automatic methods, often referred to as Neural Architecture Search (NAS), in designing neural network architectures has recently drawn considerable attention. In this wo…