Name
Abstract | ||
|---|---|---|
In recent years, artificial intelligence (AI) techniques have been increasingly adopted to tackle networking problems. Although AI algorithms can deliver high-quality solutions, most of them are inherently intricate and erratic for human cognition. This lack of interpretability tremendously hinders the commercial success of AI-based solutions in practice. To cope with this challenge, networking re... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/MCOM.001.2100736 | IEEE Communications Magazine |
Keywords | DocType | Volume |
Cognition,Communication networks,Artificial intelligence,Guidelines | Journal | 60 |
Issue | ISSN | Citations |
2 | 0163-6804 | 0 |
PageRank | References | Authors |
0.34 | 9 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tianzhu Zhang | 1 | 1705 | 82.80 |
| Han Qiu | 2 | 1 | 2.38 |
| Marco Mellia | 3 | 2748 | 204.65 |
| Yuanjie Li | 4 | 243 | 38.95 |
| Hewu Li | 5 | 169 | 26.61 |
| Ke Xu | 6 | 1392 | 171.73 |