A Federated Learning-enabled Smart Street Light Monitoring Application: Benefits and Future Challenges-Reference-Cited by-同舟云学术

A Federated Learning-enabled Smart Street Light Monitoring Application: Benefits and Future Challenges

Published:2022-10-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 1st ACM Workshop on AI Empowered Mobile and Wireless Sensing
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Author:

Anand Diya¹,Mavromatis Ioannis²^ORCID,Carnelli Pietro³^ORCID,Khan Aftab³^ORCID

Affiliation:

1. Electrical and Electronic Engineering, University of Bristol, Bristol, United Kingdom

2. Toshiba Europe Ltd, Bristol, United Kingdom

3. Toshiba Europe Limited, Bristol, United Kingdom

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3556558.3558580

Reference26 articles.

1. Methods and Systems for Remote Training of a Machine Learning Model;Anwar Saif;US Patent App.,2022

2. System and Method for Adaptive Compression in Federated Learning;Anwar Saif;US Patent App.,2022

3. F. Chen M. Luo Z. Dong Z. Li and X. He. 2018. Federated meta-learning with fast convergence and efficient communication. arXiv preprint (2018). F. Chen M. Luo Z. Dong Z. Li and X. He. 2018. Federated meta-learning with fast convergence and efficient communication. arXiv preprint (2018).

4. IoT Connectivity Technologies and Applications: A Survey

5. UMBRELLA Collaborative Robotics Testbed and IoT Platform

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