113 citations · 229 across the 41 of their papers we have counts for
3 papers · 1 filter
Robust Learning Protocol for Federated Tumor Segmentation Challenge
Ambrish Rawat, Giulio Zizzo, Swanand Kadhe +2
In this work, we devise robust and efficient learning protocols for orchestrating a Federated Learning (FL) process for the Federated Tumor Segmentation Challenge (FeTS 2022). Enab…
DeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust Setting
Runhua Xu, Nathalie Baracaldo, Yi Zhou +3
Federated learning has emerged as a privacy-preserving machine learning approach where multiple parties can train a single model without sharing their raw training data. Federated…
Federated Unlearning: How to Efficiently Erase a Client in FL?
Anisa Halimi, Swanand Kadhe, Ambrish Rawat +1
With privacy legislation empowering the users with the right to be forgotten, it has become essential to make a model amenable for forgetting some of its training data. However, ex…