Considerations on the Theory of Training Models with Differential
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Considerations on the Theory of Training Models with Differential Privacy

8 March 2023

Marten van Dijk

Phuong Ha Nguyen

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Papers citing "Considerations on the Theory of Training Models with Differential Privacy"

18 / 18 papers shown

Title
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 301 30,152 0 01 Mar 2022
F1: A Fast and Programmable Accelerator for Fully Homomorphic Encryption (Extended Version) Axel S. Feldmann Nikola Samardzic A. Krastev S. Devadas R. Dreslinski Karim M. El Defrawy Nicholas Genise Chris Peikert Daniel Sánchez 126 262 0 11 Sep 2021
CrypTen: Secure Multi-Party Computation Meets Machine Learning Brian Knott Shobha Venkataraman Awni Y. Hannun Shubho Sengupta Mark Ibrahim Laurens van der Maaten 94 364 0 02 Sep 2021
Optimal Accounting of Differential Privacy via Characteristic Function Yuqing Zhu Jinshuo Dong Yu Wang 55 104 0 16 Jun 2021
Inverting Gradients -- How easy is it to break privacy in federated learning? Jonas Geiping Hartmut Bauermeister Hannah Dröge Michael Moeller FedML 121 1,234 0 31 Mar 2020
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 281 444 0 04 Mar 2020
iDLG: Improved Deep Leakage from Gradients Bo Zhao Konda Reddy Mopuri Hakan Bilen FedML 81 643 0 08 Jan 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 279 6,307 0 10 Dec 2019
Differentially Private Model Publishing for Deep Learning Lei Yu Ling Liu C. Pu Mehmet Emre Gursoy Stacey Truex FedML 92 268 0 03 Apr 2019
Towards Federated Learning at Scale: System Design Keith Bonawitz Hubert Eichner W. Grieskamp Dzmitry Huba A. Ingerman ... H. B. McMahan Timon Van Overveldt David Petrou Daniel Ramage Jason Roselander FedML 128 2,676 0 04 Feb 2019
New Convergence Aspects of Stochastic Gradient Algorithms Lam M. Nguyen Phuong Ha Nguyen Peter Richtárik K. Scheinberg Martin Takáč Marten van Dijk 127 66 0 10 Nov 2018
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 280 4,168 0 18 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 147 1,910 0 08 Oct 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 220 6,172 0 01 Jul 2016
Revisiting Distributed Synchronous SGD Jianmin Chen Xinghao Pan R. Monga Samy Bengio Rafal Jozefowicz 89 801 0 04 Apr 2016
Concentrated Differential Privacy Cynthia Dwork G. Rothblum 82 453 0 06 Mar 2016
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization Xiangru Lian Yijun Huang Y. Li Ji Liu 147 499 0 27 Jun 2015
Near-Optimal Algorithms for Differentially-Private Principal Components Kamalika Chaudhuri Anand D. Sarwate Kaushik Sinha 115 158 0 12 Jul 2012