Name
Abstract | ||
|---|---|---|
Neural architecture search (NAS) has emerged as a promising avenue for automatically designing task-specific neural networks. Existing NAS approaches require one complete search for each deployment specification of hardware or objective. This is a computationally impractical endeavor given the potentially large number of application scenarios. In this paper, we propose Neural Architecture ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TPAMI.2021.3052758 | IEEE Transactions on Pattern Analysis and Machine Intelligence |
Keywords | DocType | Volume |
Computer architecture,Task analysis,Search problems,Predictive models,Computational modeling,Training,Neural networks | Journal | 43 |
Issue | ISSN | Citations |
9 | 0162-8828 | 7 |
PageRank | References | Authors |
0.42 | 12 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhichao Lu | 1 | 58 | 5.93 |
| Sreekumar Gautam | 2 | 7 | 0.42 |
| Erik Goodman | 3 | 145 | 15.19 |
| Wolfgang Banzhaf | 4 | 2627 | 367.13 |
| Kalyanmoy Deb | 5 | 21058 | 1398.01 |
| Vishnu Naresh Boddeti | 6 | 166 | 15.62 |