Interpretable Feature Learning in Multivariate Big Data Analysis for Network Monitoring-Reference-Cited by-同舟云学术

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Interpretable Feature Learning in Multivariate Big Data Analysis for Network Monitoring

Published:2024-06 Issue:3 Volume:21 Page:2926-2943
ISSN:1932-4537
Container-title:IEEE Transactions on Network and Service Management
language:
Short-container-title:IEEE Trans. Netw. Serv. Manage.

Author:

Camacho José¹^ORCID,Wasielewska Katarzyna¹^ORCID,Bro Rasmus²^ORCID,Kotz David³^ORCID

Affiliation:

1. Research Centre for Information and Communication Technologies (CITIC-UGR), University of Granada, Granada, Spain

2. Chemometrics Group, University of Copenhagen, Copenhagen, Denmark

3. Department of Computer Science, Dartmouth College, Hanover, NH, USA

Funder

Dartmouth effort

ACM SIGMOBILE

US National Science Foundation

Agencia Estatal de Investigación in Spain

European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie

Universidad de Granada/CBUA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

https://ieeexplore.ieee.org/ielam/4275028/10599562/10445280-aam.pdf

Reference75 articles.

1. Deep Learning for Anomaly Detection

2. Towards a rigorous science of interpretable machine learning;Doshi-Velez;arXiv:1702.08608,2017

3. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead

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