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FML: Fast Machine Learning for 5G mmWave Vehicular Communications

Asadiand, Arash and Müller, Sabrina and Sim, Gek Hong and Klein, Anja and Matthias, Hollick (2018):
FML: Fast Machine Learning for 5G mmWave Vehicular Communications.
In: IEEE INFOCOM 2018 - IEEE Conference on Computer Communications, DOI: 10.1109/INFOCOM.2018.8485876,
[Conference or Workshop Item]

Item Type: Conference or Workshop Item
Erschienen: 2018
Creators: Asadiand, Arash and Müller, Sabrina and Sim, Gek Hong and Klein, Anja and Matthias, Hollick
Title: FML: Fast Machine Learning for 5G mmWave Vehicular Communications
Language: English
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Sichere Mobile Netze
DFG-Collaborative Research Centres (incl. Transregio)
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > B: Adaptation Mechanisms
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > B: Adaptation Mechanisms > Subproject B3: Economics of Adaption
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > C: Communication Mechanisms
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > C: Communication Mechanisms > Subproject C1: Network-centred perspective
Event Title: IEEE INFOCOM 2018 - IEEE Conference on Computer Communications
Date Deposited: 25 Feb 2019 13:26
DOI: 10.1109/INFOCOM.2018.8485876
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