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Comparison of Statistical and Machine Learning-Based Approaches for Telemetry Data Size Reduction

descriptionPublicationkeyboard_double_arrow_right Article , Presentation , Conference object , Other literature type 02 Jul 2023 Spain Publisher:IEEEJournal:2023 23rd International Conference on Transparent Optical Networks (ICTON)Funded by:EC | DESIRE6G
Authors: Ruiz, Marc; El Sayed, Ahmad; Harb, Hassan; Velasco, Luis;

doi: 10.1109/icton59386.2023.10207348 , 10.5281/zenodo.10044425 , 10.5281/zenodo.7893131 , 10.5281/zenodo.10044426 , 10.5281/zenodo.7893130

handle: 2117/397620

Comparison of Statistical and Machine Learning-Based Approaches for Telemetry Data Size Reduction

Keywords

Dades -- Compressió (Informàtica), Auto-Encoders, Compression, Telemetry data, Statistical Similarity, B5G, Neural networks (Computer science), Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors, Data compression (Computer science), Machine learning, Aprenentatge automàtic, Xarxes neuronals (Informàtica), Statistical similarity, Telemetry Data, Auto-encoders

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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92
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