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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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The Future of Digital Health with Federated Learning

Mar 18, 2020
Nicola Rieke, Jonny Hancox, Wenqi Li, Fausto Milletari, Holger Roth, Shadi Albarqouni, Spyridon Bakas, Mathieu N. Galtier, Bennett Landman, Klaus Maier-Hein, Sebastien Ourselin, Micah Sheller, Ronald M. Summers, Andrew Trask, Daguang Xu, Maximilian Baust, M. Jorge Cardoso

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Scaling shared model governance via model splitting

Dec 14, 2018
Miljan Martic, Jan Leike, Andrew Trask, Matteo Hessel, Shane Legg, Pushmeet Kohli

* 9 pages 

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A generic framework for privacy preserving deep learning

Nov 13, 2018
Theo Ryffel, Andrew Trask, Morten Dahl, Bobby Wagner, Jason Mancuso, Daniel Rueckert, Jonathan Passerat-Palmbach

* PPML 2018, 5 pages 

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Sample Efficient Adaptive Text-to-Speech

Sep 27, 2018
Yutian Chen, Yannis Assael, Brendan Shillingford, David Budden, Scott Reed, Heiga Zen, Quan Wang, Luis C. Cobo, Andrew Trask, Ben Laurie, Caglar Gulcehre, Aäron van den Oord, Oriol Vinyals, Nando de Freitas

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Neural Arithmetic Logic Units

Aug 01, 2018
Andrew Trask, Felix Hill, Scott Reed, Jack Rae, Chris Dyer, Phil Blunsom

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sense2vec - A Fast and Accurate Method for Word Sense Disambiguation In Neural Word Embeddings

Nov 19, 2015
Andrew Trask, Phil Michalak, John Liu

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Modeling Order in Neural Word Embeddings at Scale

Jun 11, 2015
Andrew Trask, David Gilmore, Matthew Russell

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