Applications of Federated Learning in IoT for Hyper Personalisation

Veer Dosi
9/28/2023
cs.LG

No confident code implementation found for this paper.

Abstract

Billions of IoT devices are being deployed, taking advantage of faster internet, and the opportunity to access more endpoints. Vast quantities of data are being generated constantly by these devices but are not effectively being utilised. Using FL training machine learning models over these multiple clients without having to bring it to a central server. We explore how to use such a model to implement ultra levels of personalization unlike before

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Cite this paper

@article{dosi2023applications,
  title  = {Applications of Federated Learning in IoT for Hyper Personalisation},
  author = {Veer Dosi},
  year   = {2023},
  eprint = {2309.16854},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2309.16854v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2309.16854.svg)](https://codeofpaper.com/paper/2309.16854)

Discussion