Edge-cloud Collaborative Learning with Federated and Centralized Features

Author:

Li Zexi1ORCID,Li Qunwei2ORCID,Zhou Yi3ORCID,Zhong Wenliang2ORCID,Zhang Guannan2ORCID,Wu Chao1ORCID

Affiliation:

1. Zhejiang University, Hangzhou, China

2. Ant Group, Hangzhou, China

3. The University of Utah, Salt Lake City, UT, USA

Funder

the Program of Zhejiang Province Science and Technology

the University Synergy Innovation Program of Anhui Province

Academy Of Social Governance Zhejiang University

the National Key Research and Development Project of China

the National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

ACM

Reference28 articles.

1. Deep Learning with Differential Privacy

2. Hédy Attouch , Jérôme Bolte , Patrick Redont , and Antoine Soubeyran . 2010. Proximal alternating minimization and projection methods for nonconvex problems: An approach based on the Kurdyka-Łojasiewicz inequality. Mathematics of operations research , Vol. 35 , 2 ( 2010 ), 438--457. Hédy Attouch, Jérôme Bolte, Patrick Redont, and Antoine Soubeyran. 2010. Proximal alternating minimization and projection methods for nonconvex problems: An approach based on the Kurdyka-Łojasiewicz inequality. Mathematics of operations research, Vol. 35, 2 (2010), 438--457.

3. Proximal alternating linearized minimization for nonconvex and nonsmooth problems

4. Towards federated learning at scale: System design;Bonawitz Keith;Proceedings of Machine Learning and Systems,2019

5. FedGraph: Federated Graph Learning With Intelligent Sampling

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