COVID-19 Imaging Data Privacy by Federated Learning Design: A Theoretical Framework
Authors: Anwaar Ulhaq, Oliver Burmeister | Published: 2020-10-13
連合学習システム
Differentially Private Secure Multi-Party Computation for Federated Learning in Financial Applications
Authors: David Byrd, Antigoni Polychroniadou | Published: 2020-10-12
ARIANN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing
Authors: Théo Ryffel, Pierre Tholoniat, David Pointcheval, Francis Bach | Published: 2020-06-08 | Updated: 2021-10-28
Large-Scale Secure XGB for Vertical Federated Learning
Authors: Wenjing Fang, Derun Zhao, Jin Tan, Chaochao Chen, Chaofan Yu, Li Wang, Lei Wang, Jun Zhou, Benyu Zhang | Published: 2020-05-18 | Updated: 2021-09-02
A Secure Federated Learning Framework for 5G Networks
Authors: Yi Liu, Jialiang Peng, Jiawen Kang, Abdullah M. Iliyasu, Dusit Niyato, Ahmed A. Abd El-Latif | Published: 2020-05-12
Cloud-based Federated Boosting for Mobile Crowdsensing
Authors: Zhuzhu Wang, Yilong Yang, Yang Liu, Ximeng Liu, Brij B. Gupta, Jianfeng Ma | Published: 2020-05-09
Information-Theoretic Bounds on the Generalization Error and Privacy Leakage in Federated Learning
Authors: Semih Yagli, Alex Dytso, H. Vincent Poor | Published: 2020-05-05
Differentially Private Federated Learning with Laplacian Smoothing
Authors: Zhicong Liang, Bao Wang, Quanquan Gu, Stanley Osher, Yuan Yao | Published: 2020-05-01 | Updated: 2021-09-10
Private Dataset Generation Using Privacy Preserving Collaborative Learning
Authors: Amit Chaulwar | Published: 2020-04-28
Knowledge Federation: A Unified and Hierarchical Privacy-Preserving AI Framework
Authors: Hongyu Li, Dan Meng, Hong Wang, Xiaolin Li | Published: 2020-02-05 | Updated: 2020-05-22