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Group privacy for personalized federated learning

7 June 2022

Papers citing "Group privacy for personalized federated learning"

38 / 38 papers shown

Title
Tight Accounting in the Shuffle Model of Differential Privacy A. Koskela Mikko A. Heikkilä Antti Honkela FedML 49 17 0 01 Jun 2021
The Laplace Mechanism has optimal utility for differential privacy over continuous queries Natasha Fernandes Annabelle McIver Carroll Morgan 77 22 0 15 May 2021
Differentially Private Histograms in the Shuffle Model from Fake Users Albert Cheu M. Zhilyaev FedML 104 28 0 06 Apr 2021
Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling Vitaly Feldman Audra McMillan Kunal Talwar FedML 81 162 0 23 Dec 2020
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings Vinith Suriyakumar Nicolas Papernot Anna Goldenberg Marzyeh Ghassemi OOD 74 67 0 13 Oct 2020
Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT A. Koskela Hibiki Ito Lukas Prediger Antti Honkela 48 59 0 12 Jun 2020
An Efficient Framework for Clustered Federated Learning Avishek Ghosh Jichan Chung Dong Yin Kannan Ramchandran FedML 87 869 0 07 Jun 2020
LDP-Fed: Federated Learning with Local Differential Privacy Stacey Truex Ling Liu Ka-Ho Chow Mehmet Emre Gursoy Wenqi Wei FedML 66 395 0 05 Jun 2020
Local Differential Privacy based Federated Learning for Internet of Things Yang Zhao Jun Zhao Mengmeng Yang Teng Wang Ning Wang Lingjuan Lyu Dusit Niyato Kwok-Yan Lam 86 301 0 19 Apr 2020
Adaptive Federated Optimization Sashank J. Reddi Zachary B. Charles Manzil Zaheer Zachary Garrett Keith Rush Jakub Konecný Sanjiv Kumar H. B. McMahan FedML 190 1,452 0 29 Feb 2020
Three Approaches for Personalization with Applications to Federated Learning Yishay Mansour M. Mohri Jae Hun Ro A. Suresh FedML 135 579 0 25 Feb 2020
Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Shuang Song Kunal Talwar Abhradeep Thakurta 72 84 0 10 Jan 2020
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints Felix Sattler K. Müller Wojciech Samek FedML 161 1,008 0 04 Oct 2019
Federated Learning: Challenges, Methods, and Future Directions Tian Li Anit Kumar Sahu Ameet Talwalkar Virginia Smith FedML 132 4,543 0 21 Aug 2019
Deep Leakage from Gradients Ligeng Zhu Zhijian Liu Song Han FedML 105 2,227 0 21 Jun 2019
Differentially Private Learning with Adaptive Clipping Galen Andrew Om Thakkar H. B. McMahan Swaroop Ramaswamy FedML 100 343 0 09 May 2019
The Privacy Blanket of the Shuffle Model Borja Balle James Bell Adria Gascon Kobbi Nissim FedML 77 238 0 07 Mar 2019
LEAF: A Benchmark for Federated Settings S. Caldas Sai Meher Karthik Duddu Peter Wu Tian Li Jakub Konecný H. B. McMahan Virginia Smith Ameet Talwalkar FedML 158 1,424 0 03 Dec 2018
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 203 430 0 29 Nov 2018
Federated Learning for Mobile Keyboard Prediction Andrew Straiton Hard Kanishka Rao Zhifeng Lin Swaroop Indra Ramaswamy Youjie Li S. Augenstein Alex Schwing M. Annavaram A. Avestimehr FedML 138 1,546 0 08 Nov 2018
Distributed Differential Privacy via Shuffling Albert Cheu Adam D. Smith Jonathan R. Ullman David Zeber M. Zhilyaev FedML 109 352 0 04 Aug 2018
cpSGD: Communication-efficient and differentially-private distributed SGD Naman Agarwal A. Suresh Felix X. Yu Sanjiv Kumar H. B. McMahan FedML 136 491 0 27 May 2018
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels Zhilu Zhang M. Sabuncu NoLa 85 2,615 0 20 May 2018
Differentially Private Federated Learning: A Client Level Perspective Robin C. Geyer T. Klein Moin Nabi FedML 140 1,300 0 20 Dec 2017
Prochlo: Strong Privacy for Analytics in the Crowd Andrea Bittau Ulfar Erlingsson Petros Maniatis Ilya Mironov A. Raghunathan David Lie Mitch Rudominer Ushasree Kode J. Tinnés B. Seefeld 151 279 0 02 Oct 2017
Gradient Episodic Memory for Continual Learning David Lopez-Paz MarcÁurelio Ranzato VLM CLL 133 2,743 0 26 Jun 2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning Briland Hitaj G. Ateniese Fernando Perez-Cruz FedML 133 1,413 0 24 Feb 2017
Overcoming catastrophic forgetting in neural networks J. Kirkpatrick Razvan Pascanu Neil C. Rabinowitz J. Veness Guillaume Desjardins ... A. Grabska-Barwinska Demis Hassabis Claudia Clopath D. Kumaran R. Hadsell CLL 374 7,572 0 02 Dec 2016
Practical Secure Aggregation for Federated Learning on User-Held Data Keith Bonawitz Vladimir Ivanov Ben Kreuter Antonio Marcedone H. B. McMahan Sarvar Patel Daniel Ramage Aaron Segal Karn Seth FedML 88 506 0 14 Nov 2016
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 312 4,657 0 18 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 145 1,909 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 218 6,172 0 01 Jul 2016
Discrete Distribution Estimation under Local Privacy Peter Kairouz Kallista A. Bonawitz Daniel Ramage 77 330 0 24 Feb 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 412 17,615 0 17 Feb 2016
Optimal Geo-Indistinguishable Mechanisms for Location Privacy N. E. Bordenabe K. Chatzikokolakis C. Palamidessi 102 277 0 20 Feb 2014
An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks Ian Goodfellow M. Berk Mirza Xia Da Aaron Courville Yoshua Bengio 159 1,455 0 21 Dec 2013
Geo-Indistinguishability: Differential Privacy for Location-Based Systems M. Andrés N. E. Bordenabe K. Chatzikokolakis C. Palamidessi 121 1,187 0 10 Dec 2012
What Can We Learn Privately? S. Kasiviswanathan Homin K. Lee Kobbi Nissim Sofya Raskhodnikova Adam D. Smith 137 1,474 0 06 Mar 2008