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With the increasing number of data collectors such as smartphones, immense amounts of data are available.
Gradient-based learning applied to document recognition
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Alex Krizhevsky · 2012
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Privacy in pharmacogenetics: An end-to-end case study of personalized warfarin dosing
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Model inversion attacks that exploit confidence information and basic countermeasures
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Federated learning of deep networks using model averaging
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Infrastructure and distributed learning methodology for privacy-preserving multi-centric rapid learning health care: eurocat
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Arthur Jochems, Timo M. Deist, Issam El Naqa, Marc Kessler, Chuck Mayo, Jackson Reeves, Shruti Jolly, Martha Matuszak, Randall Ten Haken, Johan van Soest, Cary Oberije, Corinne Faivre-Finn, Gareth Price, Dirk de Ruysscher, Philippe Lambin, and Andre Dekker · 2017
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Privacy-preserving deep learning: Revisited and enhanced
Le Trieu Phong, Yoshinori Aono, Takuya Hayashi, Lihua Wang, and Shiho Moriai · 2017
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Deep models under the GAN: information leakage from collaborative deep learning
Briland Hitaj, Giuseppe Ateniese, and Fernando Pérez-Cruz · 2017
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Targeted backdoor attacks on deep learning systems using data poisoning
Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, and Dawn Song · 2017
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Badnets: Identifying vulnerabilities in the machine learning model supply chain
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General data protection regulation, 2018
Council of European Union · 2018
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Federated learning for mobile keyboard prediction
Andrew Hard, Kanishka Rao, Rajiv Mathews, Françoise Beaufays, Sean Augenstein, Hubert Eichner, Chloé Kiddon, and Daniel Ramage · 2018
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Federated learning for emoji prediction in a mobile keyboard
Swaroop Ramaswamy, Rajiv Mathews, Kanishka Rao, and Françoise Beaufays · 2019
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Patient clustering improves efficiency of federated machine learning to predict mortality and hospital stay time using distributed electronic medical records
Li Huang, Andrew L. Shea, Huining Qian, Aditya Masurkar, Hao Deng, and Dianbo Liu · 2019
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Multi-institutional deep learning modeling without sharing patient data: A feasibility study on brain tumor segmentation
Micah J. Sheller, G. Anthony Reina, Brandon Edwards, Jason Martin, and Spyridon Bakas · 2019
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Deep leakage from gradients, 2019
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Applied federated learning: Improving google keyboard query suggestions
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Federated learning of predictive models from federated electronic health records
Theodora S. Brisimi, Ruidi Chen, Theofanie Mela, Alex Olshevsky, Ioannis Ch. Paschalidis, and Wei Shi · 2018
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Beyond inferring class representatives: User-level privacy leakage from federated learning
Zhibo Wang, Mengkai Song, Zhifei Zhang, Yang Song, Qian Wang, and Hairong Qi · 2018
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How to backdoor federated learning
Eugene Bagdasaryan, Andreas Veit, Yiqing Hua, Deborah Estrin, and Vitaly Shmatikov · 2018
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The ineffectiveness of the correlation coefficient for image comparisons
K. Yen, Eugene K. Yen, Roger G. Johnston, Roger G. Johnston, and Ph. D
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Ligeng Zhu, Zhijian Liu, and Song Han · 2019
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Stefan Zwaard, Henk-Jan Boele, Hani Alers, Christos Strydis, Casey Lew-Williams, and Zaid Al-Ars · 2020
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An overview of federated deep learning privacy attacks and defensive strategies
David Enthoven and Zaid Al-Ars · 2020
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Threats to federated learning: A survey, 2020
Lingjuan Lyu, Han Yu, and Qiang Yang · 2020
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idlg: Improved deep leakage from gradients, 2020
Bo Zhao, Konda Reddy Mopuri, and Hakan Bilen · 2020
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