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Towards General-purpose Infrastructure for Protecting Scientific Data Under Study


Oct 04, 2021
Andrew Trask, Kritika Prakash


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Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation


Jul 09, 2021
Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Kritika Prakash, Andrew Trask, Rickmer Braren, Marcus Makowski, Daniel Rueckert, Georgios Kaissis

* Accepted to the ICML 2021 Theory and Practice of Differential Privacy Workshop 

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DP-SGD vs PATE: Which Has Less Disparate Impact on Model Accuracy?


Jun 22, 2021
Archit Uniyal, Rakshit Naidu, Sasikanth Kotti, Sahib Singh, Patrik Joslin Kenfack, Fatemehsadat Mireshghallah, Andrew Trask

* 4 pages, 3 images 

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Syft 0.5: A Platform for Universally Deployable Structured Transparency


Apr 27, 2021
Adam James Hall, Madhava Jay, Tudor Cebere, Bogdan Cebere, Koen Lennart van der Veen, George Muraru, Tongye Xu, Patrick Cason, William Abramson, Ayoub Benaissa, Chinmay Shah, Alan Aboudib, Théo Ryffel, Kritika Prakash, Tom Titcombe, Varun Kumar Khare, Maddie Shang, Ionesio Junior, Animesh Gupta, Jason Paumier, Nahua Kang, Vova Manannikov, Andrew Trask

* ICLR 2021 Workshop on Distributed and Private Machine Learning (DPML 2021) 

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Privacy-preserving medical image analysis


Dec 10, 2020
Alexander Ziller, Jonathan Passerat-Palmbach, Théo Ryffel, Dmitrii Usynin, Andrew Trask, Ionésio Da Lima Costa Junior, Jason Mancuso, Marcus Makowski, Daniel Rueckert, Rickmer Braren, Georgios Kaissis

* Accepted at the workshop for Medical Imaging meets NeurIPS, 34th Conference on Neural Information Processing Systems (NeurIPS) December 11, 2020 

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Neither Private Nor Fair: Impact of Data Imbalance on Utility and Fairness in Differential Privacy


Oct 03, 2020
Tom Farrand, Fatemehsadat Mireshghallah, Sahib Singh, Andrew Trask

* 5 pages, 5 figures 

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Benchmarking Differentially Private Residual Networks for Medical Imagery


Jun 28, 2020
Sahib Singh, Harshvardhan Sikka, Sasikanth Kotti, Andrew Trask

* 5 Pages, 3 Figures 

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