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Random Forests Resource Allocation for 5G Systems: Performance and Robustness Study
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
KTH, School of Electrical Engineering (EES), Information Science and Engineering.ORCID iD: 0000-0001-6682-6559
2018 (English)Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
2018.
National Category
Engineering and Technology
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-223418DOI: 10.1109/WCNCW.2018.8369028ISI: 000442393300056Scopus ID: 2-s2.0-85048899054OAI: oai:DiVA.org:kth-223418DiVA, id: diva2:1184298
Conference
International Workshop on Big Data with Computational Intelligence for Wireless Networking (IEEE WCNC BDCIWN)
Note

QC 20180327

Available from: 2018-02-21 Created: 2018-02-21 Last updated: 2018-09-11Bibliographically approved

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fulltext(926 kB)12 downloads
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File name FULLTEXT01.pdfFile size 926 kBChecksum SHA-512
739d1972d5f2aac4dc14c34673db02255a567f78fe0e1bb43dc211a20ad87b39f30551b542e59c4797bd35ff90e2c3229fc4cab15fea073704c4f602a7c38282
Type fulltextMimetype application/pdf

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Imtiaz, SaharGhauch, HadiGross, James
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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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