Efficient Federated Learning With Enhanced Privacy via Lottery Ticket Pruning in Edge Computing-Reference-Cited by-同舟云学术

Efficient Federated Learning With Enhanced Privacy via Lottery Ticket Pruning in Edge Computing

Author:

Shi Yifan¹^ORCID,Wei Kang²^ORCID,Shen Li³^ORCID,Li Jun⁴^ORCID,Wang Xueqian¹^ORCID,Yuan Bo⁵^ORCID,Guo Song⁶^ORCID

Affiliation:

1. Center for Artificial Intelligence and Robotics, Shenzhen International Graduate School, Tsinghua University, Shenzhen, China

2. Department of Computing, Hong Kong Polytechnic University, Hong Kong, SAR, China

3. JD Explore Academy, Beijing, China

4. School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China

5. Research Institute of Tsinghua, University in Shenzhen, Shenzhen, China

6. Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Key Technologies R&D Program of Jiangsu

Key-Area Research and Development Program of Guangdong Province

Hong Kong RGC Research Impact Fund

Areas of Excellence Scheme

General Research Fund

Shenzhen Science and Technology Innovation Commission

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

Reference48 articles.

2. Communication-efficient learning of deep networks from decentralized data;McMahan

5. FedBoost: A communication-efficient algorithm for federated learning;Hamer

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