Federated Self-Supervised Learning in Heterogeneous Settings: Limits of a Baseline Approach on HAR-Reference-Cited by-同舟云学术

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Federated Self-Supervised Learning in Heterogeneous Settings: Limits of a Baseline Approach on HAR

Published:2022-03-21 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)
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Author:

Ek Sannara¹,Rombourg Romain¹,Portet Francois¹,Lalanda Philippe¹

Affiliation:

1. Univ. Grenoble Alpes,CNRS,Grenoble,France,LIG F-38000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9766442/9767206/09767369.pdf?arnumber=9767369

Reference24 articles.

1. Towards federated unsupervised representation learning

2. A survey on federated learning systems: Vision, hype and reality for data privacy and protection;li;IEEE Transactions on Knowledge & Data Engineering,5555

3. A public domain dataset for human activity recognition using smartphones;anguita;21st European Symposium on Artificial Neural Networks ESANN 2013,2013

4. Smart Devices are Different

5. On-body localization of wearable devices: An investigation of position-aware activity recognition

Cited by 1 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. A Client Selection Method Based on Loss Function Optimization for Federated Learning;Computer Modeling in Engineering & Sciences;2023

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