86 citations · 203 across the 5 of their papers we have counts for
5 papers
SCARLET-NAS: Bridging the Gap between Stability and Scalability in Weight-sharing Neural Architecture Search
Xiangxiang Chu, Bo Zhang, Qingyuan Li +2
To discover powerful yet compact models is an important goal of neural architecture search. Previous two-stage one-shot approaches are limited by search space with a fixed depth. I…
MoGA: Searching Beyond MobileNetV3
Xiangxiang Chu, Bo Zhang, Ruijun Xu
The evolution of MobileNets has laid a solid foundation for neural network applications on mobile end. With the latest MobileNetV3, neural architecture search again claimed its sup…
FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture Search
Xiangxiang Chu, Bo Zhang, Ruijun Xu
One of the most critical problems in weight-sharing neural architecture search is the evaluation of candidate models within a predefined search space. In practice, a one-shot super…
Multi-Objective Reinforced Evolution in Mobile Neural Architecture Search
Xiangxiang Chu, Bo Zhang, Ruijun Xu +1
Fabricating neural models for a wide range of mobile devices demands for a specific design of networks due to highly constrained resources. Both evolution algorithms (EA) and reinf…
Fast, Accurate and Lightweight Super-Resolution with Neural Architecture Search
Xiangxiang Chu, Bo Zhang, Hailong Ma +2
Deep convolutional neural networks demonstrate impressive results in the super-resolution domain. A series of studies concentrate on improving peak signal noise ratio (PSNR) by usi…