| Residential College | false |
| Status | 已發表Published |
| FedGCS: A Generative Framework for Effcient Client Selection in Federated Learning via Gradient-based Optimization | |
ZHIYUAN NING1,2; CHUNLIN TIAN4; MENG XIAO1,2; WEI FAN5; PENGYANG WANG4 ; LI LI4; PENGFEI WANG1,2; YUANCHUN ZHOU1,2,3
| |
| 2024-08 | |
| Conference Name | The 33rd International Joint Conference on Artificial Intelligence |
| Conference Date | 2024-08-03 |
| Conference Place | Jeju, South Korea |
| Document Type | Conference paper |
| Collection | THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU) |
| Affiliation | 1.Computer Network Information Center, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences 3.Hangzhou Institute for Advanced Study, UCAS 4.Department of Computer and Information Science, IOTSC, University of Macau 5.University of Oxford |
| Recommended Citation GB/T 7714 | ZHIYUAN NING,CHUNLIN TIAN,MENG XIAO,et al. FedGCS: A Generative Framework for Effcient Client Selection in Federated Learning via Gradient-based Optimization[C], 2024. |
| APA | ZHIYUAN NING., CHUNLIN TIAN., MENG XIAO., WEI FAN., PENGYANG WANG., LI LI., PENGFEI WANG., & YUANCHUN ZHOU (2024). FedGCS: A Generative Framework for Effcient Client Selection in Federated Learning via Gradient-based Optimization. . |
| Files in This Item: | There are no files associated with this item. | |||||
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