PyramidFL

Author:

Li Chenning1,Zeng Xiao1,Zhang Mi1,Cao Zhichao1

Affiliation:

1. Michigan State University

Funder

NSF (National Science Foundation)

Publisher

ACM

Reference56 articles.

1. Deep Learning with Differential Privacy

2. Ahmed M Abdelmoniem , Atal Narayan Sahu , Marco Canini, and Suhaib A Fahmy. 2021 . Resource-Efficient Federated Learning . arXiv preprint arXiv:2111.01108 (2021). Ahmed M Abdelmoniem, Atal Narayan Sahu, Marco Canini, and Suhaib A Fahmy. 2021. Resource-Efficient Federated Learning. arXiv preprint arXiv:2111.01108 (2021).

3. Guillaume Alain , Alex Lamb , Chinnadhurai Sankar , Aaron Courville , and Yoshua Bengio . 2016. Variance Reduction in SGD by Distributed Importance Sampling. arXiv:1511.06481 [cs, stat] ( 2016 ). Guillaume Alain, Alex Lamb, Chinnadhurai Sankar, Aaron Courville, and Yoshua Bengio. 2016. Variance Reduction in SGD by Distributed Importance Sampling. arXiv:1511.06481 [cs, stat] (2016).

4. Dan Alistarh , Demjan Grubic , Jerry Li , Ryota Tomioka , and Milan Vojnovic . 2017 . QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding . In Proceedings of NeurIPS, I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett (Eds.) , Vol. 30 . Dan Alistarh, Demjan Grubic, Jerry Li, Ryota Tomioka, and Milan Vojnovic. 2017. QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding. In Proceedings of NeurIPS, I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett (Eds.), Vol. 30.

5. Keith Bonawitz , Hubert Eichner , Wolfgang Grieskamp , Dzmitry Huba , Alex Ingerman , Vladimir Ivanov , Chloe Kiddon , Jakub Konečnỳ , Stefano Mazzocchi , H Brendan McMahan , 2019 . Towards federated learning at scale: System design . In Proceedings of MLSys. Keith Bonawitz, Hubert Eichner, Wolfgang Grieskamp, Dzmitry Huba, Alex Ingerman, Vladimir Ivanov, Chloe Kiddon, Jakub Konečnỳ, Stefano Mazzocchi, H Brendan McMahan, et al. 2019. Towards federated learning at scale: System design. In Proceedings of MLSys.

Cited by 63 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Recent advances on federated learning: A systematic survey;Neurocomputing;2024-09

2. FedRoLA: Robust Federated Learning Against Model Poisoning via Layer-based Aggregation;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

3. Device Selection Methods in Federated Learning: A Survey;SN Computer Science;2024-08-02

4. A comprehensive survey of federated transfer learning: challenges, methods and applications;Frontiers of Computer Science;2024-07-23

5. Can Federated Learning Clients be Lightweight? A Plug-and-Play Symmetric Conversion Module;2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS);2024-07-23

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3