Fed-NL: A Federated Learning Approach to Suppress Noise in Participant Datasets to Reduce Communication Rounds for Convergence

Fed-NL: A Federated Learning Approach to Suppress Noise in Participant Datasets to Reduce Communication Rounds for Convergence. Mishra, R. & Gupta, H. P. IEEE Trans. Mob. Comput., 24(9):8245–8257, 2025.

Paper doi bibtex

@article{DBLP:journals/tmc/MishraG25a,
  author       = {Rahul Mishra and
                  Hari Prabhat Gupta},
  title        = {Fed-NL: {A} Federated Learning Approach to Suppress Noise in Participant
                  Datasets to Reduce Communication Rounds for Convergence},
  journal      = {{IEEE} Trans. Mob. Comput.},
  volume       = {24},
  number       = {9},
  pages        = {8245--8257},
  year         = {2025},
  url          = {https://doi.org/10.1109/TMC.2025.3558874},
  doi          = {10.1109/TMC.2025.3558874},
  timestamp    = {Sat, 06 Sep 2025 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/journals/tmc/MishraG25a.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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