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2006.10517
Cited By
Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention
15 June 2020
Ce Ju
Ruihui Zhao
Jichao Sun
Xiguang Wei
Bo Zhao
Yang Liu
Hongshan Li
Tianjian Chen
Xinwei Zhang
Dashan Gao
Ben Tan
Han Yu
Chuning He
Yuan Jin
FedML
OOD
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Papers citing
"Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention"
7 / 7 papers shown
Title
Federated Transfer Learning for EEG Signal Classification
Ce Ju
Dashan Gao
R. Mane
Ben Tan
Yang Liu
Cuntai Guan
FedML
41
107
0
26 Apr 2020
Advances and Open Problems in Federated Learning
Peter Kairouz
H. B. McMahan
Brendan Avent
A. Bellet
M. Bennis
...
Zheng Xu
Qiang Yang
Felix X. Yu
Han Yu
Sen Zhao
FedML
AI4CE
212
6,229
0
10 Dec 2019
Privacy-preserving Federated Brain Tumour Segmentation
Wenqi Li
Fausto Milletarì
Daguang Xu
Nicola Rieke
Jonny Hancox
...
Maximilian Baust
Yan Cheng
Sébastien Ourselin
M. Jorge Cardoso
Andrew Feng
FedML
73
477
0
02 Oct 2019
HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography
Dashan Gao
Ce Ju
Xiguang Wei
Yang Liu
Tianjian Chen
Qiang Yang
FedML
110
91
0
11 Sep 2019
Multi-Institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation
Micah J. Sheller
G. A. Reina
Brandon Edwards
Jason Martin
Spyridon Bakas
FedML
61
465
0
10 Oct 2018
Federated Optimization: Distributed Machine Learning for On-Device Intelligence
Jakub Konecný
H. B. McMahan
Daniel Ramage
Peter Richtárik
FedML
126
1,895
0
08 Oct 2016
XGBoost: A Scalable Tree Boosting System
Tianqi Chen
Carlos Guestrin
735
38,858
0
09 Mar 2016
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