Personalized and differentially private federated learning for mobility data mining via the TrajectoryGuard framework

Ali Alqazzaz

Open source

DOI: 10.1371/journal.pone.0358703
Published: 2026-10-29
Container: PLOS One
Publisher: Public Library of Science (PLoS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0358703,
  title = {Personalized and differentially private federated learning for mobility data mining via the TrajectoryGuard framework},
  author = {Ali Alqazzaz},
  year = {2026},
  journal = {PLOS One},
  doi = {10.1371/journal.pone.0358703},
  url = {https://doi.org/10.1371/journal.pone.0358703}
}

RIS

TY  - JOUR
TI  - Personalized and differentially private federated learning for mobility data mining via the TrajectoryGuard framework
AU  - Ali Alqazzaz
PY  - 2026
JO  - PLOS One
DO  - 10.1371/journal.pone.0358703
UR  - https://doi.org/10.1371/journal.pone.0358703
ER  -

APA

Alqazzaz, A. (2026). Personalized and differentially private federated learning for mobility data mining via the TrajectoryGuard framework. PLOS One. https://doi.org/10.1371/journal.pone.0358703

Source records

crossref · retrieved 2026-11-10T10:15:59.014Z