Privacy Preservation in Federated Learning: An insightful survey from
the GDPR Perspective

Privacy Preservation in Federated Learning: An insightful survey from the GDPR Perspective

10 November 2020

Florian Guitton

Papers citing "Privacy Preservation in Federated Learning: An insightful survey from the GDPR Perspective"

9 / 9 papers shown

Title
Privacy-Preserving Collaborative Split Learning Framework for Smart Grid Load Forecasting Asif Iqbal P. Gope Biplab Sikdar 41 2 0 03 Mar 2024
MAPSeg: Unified Unsupervised Domain Adaptation for Heterogeneous Medical Image Segmentation Based on 3D Masked Autoencoding and Pseudo-Labeling Xuzhe Zhang Yu-Hsun Wu S. Entringer H. Simhan Jia Guo ... A. Jackowski Haifeng Li J. Posner Andrew F. Laine Yun Wang OOD 22 11 0 16 Mar 2023
The Role of Cross-Silo Federated Learning in Facilitating Data Sharing in the Agri-Food Sector A. Durrant Milan Markovic David Matthews David May J. Enright Georgios Leontidis FedML 32 69 0 14 Apr 2021
Information Theoretic Secure Aggregation with User Dropouts Yizhou Zhao Hua Sun FedML 59 67 0 19 Jan 2021
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 349 4,237 0 23 Aug 2019
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 191 1,034 0 29 Nov 2018
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 144 1,688 0 14 Apr 2018
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 257 3,698 0 28 Feb 2017
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 310 2,896 0 15 Sep 2016