Hourglass: Enabling Efficient Split Federated Learning with Data Parallelism
Qiang He, Kaibin Wang, Zeqian Dong, Liang Yuan, Feifei Chen, Hai Jin, Yun Yang
2025年份
3被引次数
1顶会引用
问问这篇 Paper
问问你的智能体。
Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。
引用它的顶会 Paper1
问问它们各自怎么用它相关 Paper
- CA-PFL: Client-adaptive Parameter-efficient Fine-tuning for Personalized Federated LearningDaixin Song, Hui Cai, Haojie Zhang, Biyun Sheng 等WWW 2026
- Towards Geometry-Consistent Federated Graph LearningYuecen Wei, Zhiyu Zhuang, Yisen Gao, Xingcheng Fu 等WWW 2026
- No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and Server ComputationFeilong Zhang, Xianming Liu, Shiyi Lin, Gang Wu 等ICML 2023 · 被引用 15 次
- Convergence Analysis of Split Federated Learning on Heterogeneous DataPengchao Han, Chao Huang, Geng Tian, Ming Tang 等NeurIPS 2024 · 被引用 32 次
- Workflow Optimization for Parallel Split LearningJoana Tirana, Dimitra Tsigkari, George Iosifidis, Dimitris ChatzopoulosINFOCOM 2024 · 被引用 14 次
