v1v2 (latest)

Tight Lower Bounds for Locally Differentially Private Selection

7 February 2018

Jonathan R. Ullman

ArXiv (abs)PDF HTML

Papers citing "Tight Lower Bounds for Locally Differentially Private Selection"

17 / 17 papers shown

Title
Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity A. F. Pour Hassan Ashtiani S. Asoodeh 89 1 0 09 Dec 2023
When approximate design for fast homomorphic computation provides differential privacy guarantees Arnaud Grivet Sébert Martin Zuber Oana Stan Renaud Sirdey Cédric Gouy-Pailler TPM 57 1 0 06 Apr 2023
Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models Liam H. Fowl Jonas Geiping Steven Reich Yuxin Wen Wojtek Czaja Micah Goldblum Tom Goldstein FedML 131 56 0 29 Jan 2022
Unsupervised Information Obfuscation for Split Inference of Neural Networks Mohammad Samragh H. Hosseini Aleksei Triastcyn K. Azarian Joseph B. Soriaga F. Koushanfar 81 11 0 23 Apr 2021
On Distributed Differential Privacy and Counting Distinct Elements Lijie Chen Badih Ghazi Ravi Kumar Pasin Manurangsi FedML 103 32 0 21 Sep 2020
Differentially Private Clustering: Tight Approximation Ratios Badih Ghazi Ravi Kumar Pasin Manurangsi 86 54 0 18 Aug 2020
Interactive Inference under Information Constraints Jayadev Acharya C. Canonne Yuhan Liu Ziteng Sun Himanshu Tyagi 140 35 0 21 Jul 2020
SPEED: Secure, PrivatE, and Efficient Deep learning Arnaud Grivet Sébert Rafael Pinot Martin Zuber Cédric Gouy-Pailler Renaud Sirdey FedML 62 20 0 16 Jun 2020
Locally Private Hypothesis Selection Sivakanth Gopi Gautam Kamath Janardhan Kulkarni Aleksandar Nikolov Zhiwei Steven Wu Huanyu Zhang 91 27 0 21 Feb 2020
The power of synergy in differential privacy: Combining a small curator with local randomizers A. Beimel Aleksandra Korolova Kobbi Nissim Or Sheffet Uri Stemmer 70 15 0 18 Dec 2019
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 304 6,354 0 10 Dec 2019
On the Power of Multiple Anonymous Messages Badih Ghazi Noah Golowich Ravi Kumar Rasmus Pagh A. Velingker FedML 102 6 0 29 Aug 2019
Aggregating Votes with Local Differential Privacy: Usefulness, Soundness vs. Indistinguishability Shaowei Wang Jiachun Du Wei Yang Xinrong Diao Zichun Liu Yiwen Nie Liusheng Huang Hongli Xu FedML 51 7 0 14 Aug 2019
The Role of Interactivity in Local Differential Privacy Matthew Joseph Jieming Mao Seth Neel Aaron Roth 100 65 0 07 Apr 2019
Locally Private Gaussian Estimation Matthew Joseph Janardhan Kulkarni Jieming Mao Zhiwei Steven Wu FedML 96 38 0 20 Nov 2018
Distributed Differential Privacy via Shuffling Albert Cheu Adam D. Smith Jonathan R. Ullman David Zeber M. Zhilyaev FedML 153 353 0 04 Aug 2018
Local Differential Privacy for Evolving Data Matthew Joseph Aaron Roth Jonathan R. Ullman Bo Waggoner 106 87 0 20 Feb 2018