Federated Learning for Indoor Localization via Model Reliability With Dropout

  • Junha Park
  • , Jiseon Moon
  • , Taekyoon Kim
  • , Peng Wu
  • , Tales Imbiriba
  • , Pau Closas
  • , Sunwoo Kim

Research output: Contribution to journalArticlepeer-review

Original languageEnglish
Pages (from-to)1553-1557
Number of pages5
JournalIEEE Communications Letters
Volume26
Issue number7
DOIs
StatePublished - Jul 1 2022

ASJC Scopus Subject Areas

  • Modeling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering

Keywords

  • Bayesian approximation
  • Federated learning (FL)
  • indoor localization
  • model uncertainty

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