Afaf Taïk - Data-Quality Based Scheduling f. Fed. Edge Learning - IEEE LCN 2021 Best Paper Candidate
Channel: IEEE LCN
Date: 2022-09-07

This is the presentation capture of the LCN conference best paper candidate
- entitled Data-Quality Based Scheduling for Federated Edge Learning
- presented by Afaf Taïk
- all co-authors: Afaf Taïk (Université de Sherbrooke, Canada); Hajar Moudoud (Universite de Sherbrooke, Canada); Soumaya Cherkaoui (2500 Ch. Polytechnique, Canada & Polytechnique Montreal, Canada)

The best paper candidates plenary session has been held at IEEE LCN 2021 on Monday, 4 October 2021.

See more about the LCN awards at https://www.ieeelcn.org/Program_awards.html

Congratulations for receiving one of the LCN 2021 best paper awards!