Name
Abstract | ||
|---|---|---|
Deep learning models, like traditional software systems, provide a large number of configuration options. A deep learning model can be configured with different hyperparameters and neural architectures. Recently, AutoML (Automated Machine Learning) has been widely adopted to automate model training by systematically exploring diverse configurations. However, current AutoML approaches do not take i... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICSE43902.2021.00028 | 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) |
Keywords | DocType | ISSN |
Deep learning,Training,Analytical models,Computational modeling,Tools,Software systems,Software engineering | Conference | 0270-5257 |
ISBN | Citations | PageRank |
978-1-6654-0296-5 | 1 | 0.35 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yanjie Gao | 1 | 1 | 0.35 |
| Yonghao Zhu | 2 | 1 | 0.35 |
| Hongyu Zhang | 3 | 864 | 50.03 |
| Haoxiang Lin | 4 | 181 | 9.29 |
| Mao Yang | 5 | 29 | 7.41 |