Name
Abstract | ||
|---|---|---|
Neural architecture search can discover neural networks with good performance, and One-Shot approaches are prevalent. One-Shot approaches typically require a supernet with weight sharing and predictors that predict the performance of architecture. However, the previous methods take much time to generate performance predictors thus are inefficient. To this end, we propose FOX-NAS that consists of f... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICCVW54120.2021.00093 | 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) |
Keywords | DocType | Volume |
Computer vision,Costs,Search methods,Conferences,Neural networks,Graphics processing units,Computer architecture | Conference | 2021 |
Issue | ISSN | ISBN |
1 | 2473-9936 | 978-1-6654-0191-3 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chia-Hsiang Liu | 1 | 0 | 0.34 |
| Yu-Shin Han | 2 | 0 | 1.01 |
| Yuan-Yao Sung | 3 | 0 | 0.34 |
| Yi Lee | 4 | 0 | 0.34 |
| Hung-Yueh Chiang | 5 | 0 | 0.68 |
| Kai-Chiang Wu | 6 | 0 | 1.01 |