Optical Status Representation by Collaborative and Unsupervised Learning-Reference-Cited by-同舟云学术

Optical Status Representation by Collaborative and Unsupervised Learning

Published:2022-07-03 Issue: Volume: Page:
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Container-title:2022 27th OptoElectronics and Communications Conference (OECC) and 2022 International Conference on Photonics in Switching and Computing (PSC)
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Author:

Tanimura Takahito¹,Hirai Riu¹,Kikuchi Nobuhiko¹

Affiliation:

1. Research & Development Group, Hitachi Ltd.,Tokyo,Japan,185-8601

Funder

New Energy and Industrial Technology Development Organization (NEDO)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9849706/9849712/09850027.pdf?arnumber=9850027

Reference8 articles.

1. Communication-efficient learning of deep networks from decentralized data;mcmahan;Proc of 20th International Conference on Artificial Intelligence and Statistics (AISTATS),0

2. Auto-encoding variational bayes;kingma;Proc of 2nd International Conference on Learning Representations (ICLR),0

3. Vertical Federated Learning for Privacy-Preserving ML Model Development in Partially Disaggregated Networks

4. Demonstration of Federated Learning over Edge-Computing Enabled Metro Optical Networks

5. Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data

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1. Physical Status Representation in Multiple Administrative Optical Networks by Federated Unsupervised Learning;IEICE Transactions on Communications;2023-11-01

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