On Real-Time and Self-Taught Anomaly Detection in Optical Networks Using Hybrid Unsupervised/Supervised Learning-Reference-Cited by-同舟云学术

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On Real-Time and Self-Taught Anomaly Detection in Optical Networks Using Hybrid Unsupervised/Supervised Learning

Published:2018-09 Issue: Volume: Page:
ISSN:
Container-title:2018 European Conference on Optical Communication (ECOC)
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Author:

Chen X.,Li B.,Shamsabardeh M.,Proietti R.,Zhu Z.,Yoo S. J. B.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8516262/8535099/08535185.pdf?arnumber=8535185

Cited by 8 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. Meta-DPSTL: meta learning-based differentially private self-taught learning;International Journal of Machine Learning and Cybernetics;2024-05-09

2. Semi-supervised learning model synergistically utilizing labeled and unlabeled data for failure detection in optical networks;Journal of Optical Communications and Networking;2024-04-23

3. Machine-Learning-Assisted Failure Prediction in Microwave Networks based on Equipment Alarms;2023 19th International Conference on the Design of Reliable Communication Networks (DRCN);2023-04-17

4. Benchmarking Unsupervised Machine Learning for Mobile Network Anomaly Detection;2022 International Conference on Innovations in Science, Engineering and Technology (ICISET);2022-02-26

5. Failure Prediction Based on LSTM and SVM under SDON Architecture;2021 7th International Conference on Computer and Communications (ICCC);2021-12-10

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