Balancing Privacy Protection and Interpretability in Federated Learning

16 February 2023

Papers citing "Balancing Privacy Protection and Interpretability in Federated Learning"

7 / 7 papers shown

Title
Interplay between Federated Learning and Explainable Artificial Intelligence: a Scoping Review Luis M. Lopez-Ramos Florian Leiser Aditya Rastogi Steven Hicks Inga Strümke V. Madai Tobias Budig Ali Sunyaev A. Hilbert 30 1 0 07 Nov 2024
A Survey of Privacy-Preserving Model Explanations: Privacy Risks, Attacks, and Countermeasures Thanh Tam Nguyen T. T. Huynh Zhao Ren Thanh Toan Nguyen Phi Le Nguyen Hongzhi Yin Quoc Viet Hung Nguyen 68 8 0 31 Mar 2024
SoK: Taming the Triangle -- On the Interplays between Fairness, Interpretability and Privacy in Machine Learning Julien Ferry Ulrich Aïvodji Sébastien Gambs Marie-José Huguet Mohamed Siala FaML 26 5 0 22 Dec 2023
The Landscape of Modern Machine Learning: A Review of Machine, Distributed and Federated Learning Omer Subasi Oceane Bel Joseph Manzano Kevin J. Barker FedML OOD PINN 25 2 0 05 Dec 2023
Privacy-Preserving Algorithmic Recourse Sikha Pentyala Shubham Sharma Sanjay Kariyappa Freddy Lecue Daniele Magazzeni 34 5 0 23 Nov 2023
Multimodal Federated Learning in Healthcare: a Review Jacob Thrasher Alina Devkota Prasiddha Siwakotai Rohit Chivukula Pranav Poudel Chaunbo Hu Binod Bhattarai P. Gyawali 30 7 0 14 Oct 2023
The Future of Digital Health with Federated Learning Nicola Rieke Jonny Hancox Wenqi Li Fausto Milletari H. Roth ... Ronald M. Summers Andrew Trask Daguang Xu Maximilian Baust M. Jorge Cardoso OOD 174 1,707 0 18 Mar 2020