Learning discrete distributions: user vs item-level privacy

27 July 2020

Sanjiv Kumar

Papers citing "Learning discrete distributions: user vs item-level privacy"

21 / 21 papers shown

Title
Improved Bounds for Pure Private Agnostic Learning: Item-Level and User-Level Privacy Bo Li Wei Wang Peng Ye FedML 52 0 0 30 Jul 2024
Differentially Private Assouad, Fano, and Le Cam Jayadev Acharya Ziteng Sun Huanyu Zhang FedML 38 58 0 14 Apr 2020
Private Mean Estimation of Heavy-Tailed Distributions Gautam Kamath Vikrant Singhal Jonathan R. Ullman 45 99 0 21 Feb 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 92 6,177 0 10 Dec 2019
Generative Models for Effective ML on Private, Decentralized Datasets S. Augenstein H. B. McMahan Daniel Ramage Swaroop Indra Ramaswamy Peter Kairouz Mingqing Chen Rajiv Mathews Blaise Agüera y Arcas SyDa 36 182 0 15 Nov 2019
Differentially private anonymized histograms A. Suresh PICV 44 22 0 08 Oct 2019
Differentially Private SQL with Bounded User Contribution Royce J. Wilson Celia Yuxin Zhang William K. C. Lam Damien Desfontaines Daniel Simmons-Marengo Bryant Gipson 51 148 0 04 Sep 2019
Private Hypothesis Selection Mark Bun Gautam Kamath Thomas Steinke Zhiwei Steven Wu 25 90 0 30 May 2019
Inference under Information Constraints I: Lower Bounds from Chi-Square Contraction Jayadev Acharya C. Canonne Himanshu Tyagi 39 110 0 30 Dec 2018
A General Approach to Adding Differential Privacy to Iterative Training Procedures H. B. McMahan Galen Andrew Ulfar Erlingsson Steve Chien Ilya Mironov Nicolas Papernot Peter Kairouz 26 192 0 15 Dec 2018
Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning Peng Kuang Mengkai Song Zhifei Zhang Yang Song Qian Wang Hairong Qi FedML 38 780 0 03 Dec 2018
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 81 151 0 01 May 2018
Hadamard Response: Estimating Distributions Privately, Efficiently, and with Little Communication Jayadev Acharya Ziteng Sun Huanyu Zhang 33 148 0 13 Feb 2018
Differentially Private Testing of Identity and Closeness of Discrete Distributions Jayadev Acharya Ziteng Sun Huanyu Zhang 52 74 0 17 Jul 2017
Optimal Schemes for Discrete Distribution Estimation under Locally Differential Privacy Min Ye A. Barg 39 178 0 02 Feb 2017
Discrete Distribution Estimation under Local Privacy Peter Kairouz Kallista A. Bonawitz Daniel Ramage 18 327 0 24 Feb 2016
Differentially Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds Raef Bassily Adam D. Smith Abhradeep Thakurta FedML 82 371 0 27 May 2014
The Composition Theorem for Differential Privacy Peter Kairouz Sewoong Oh Pramod Viswanath 86 677 0 04 Nov 2013
Differentially Private Empirical Risk Minimization Kamalika Chaudhuri C. Monteleoni Anand D. Sarwate 85 1,482 0 01 Dec 2009
A statistical framework for differential privacy Larry A. Wasserman Shuheng Zhou 66 482 0 16 Nov 2008
What Can We Learn Privately? S. Kasiviswanathan Homin K. Lee Kobbi Nissim Sofya Raskhodnikova Adam D. Smith 88 1,459 0 06 Mar 2008