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Guidelines for Implementing and Auditing Differentially Private Systems

10 February 2020

Papers citing "Guidelines for Implementing and Auditing Differentially Private Systems"

20 / 20 papers shown

Title
From Transparency to Accountability and Back: A Discussion of Access and Evidence in AI Auditing Sarah H. Cen Rohan Alur 113 5 0 07 Oct 2024
Models Matter: Setting Accurate Privacy Expectations for Local and Central Differential Privacy Mary Anne Smart Priyanka Nanayakkara Rachel Cummings Gabriel Kaptchuk Elissa M. Redmiles 63 1 0 16 Aug 2024
Evaluating Google's Protected Audience Protocol Minjun Long David Evans 84 1 0 13 May 2024
Differentially Private Fair Binary Classifications Hrad Ghoukasian S. Asoodeh FaML 92 2 0 23 Feb 2024
Recent Advances of Differential Privacy in Centralized Deep Learning: A Systematic Survey Lea Demelius Roman Kern Andreas Trügler SyDa FedML 93 9 0 28 Sep 2023
Evaluating the Usability of Differential Privacy Tools with Data Practitioners Ivoline C. Ngong Brad Stenger Joseph P. Near Yuanyuan Feng 89 13 0 24 Sep 2023
The Complexity of Verifying Boolean Programs as Differentially Private Mark Bun Marco Gaboardi Ludmila Glinskih 73 4 0 08 Sep 2023
Composition in Differential Privacy for General Granularity Notions (Long Version) Patricia Guerra-Balboa Àlex Miranda-Pascual Javier Parra-Arnau T. Strufe 69 1 0 28 Aug 2023
Random Number Generators and Seeding for Differential Privacy N. Holohan SyDa 48 1 0 07 Jul 2023
Seeding with Differentially Private Network Information M. Rahimian Fang-Yi Yu Carlos Hurtado 71 4 0 26 May 2023
Lessons Learned: Surveying the Practicality of Differential Privacy in the Industry Gonzalo Munilla Garrido Xiaoyuan Liu Florian Matthes Basel Alomair 66 25 0 07 Nov 2022
Cactus Mechanisms: Optimal Differential Privacy Mechanisms in the Large-Composition Regime Wael Alghamdi S. Asoodeh Flavio du Pin Calmon O. Kosut Lalitha Sankar Fei Wei 43 10 0 25 Jun 2022
Differentially-Private Sublinear-Time Clustering Jeremiah Blocki Elena Grigorescu Tamalika Mukherjee 51 6 0 27 Dec 2021
Privacy Budget Scheduling Tao Luo Mingen Pan Pierre Tholoniat Asaf Cidon Roxana Geambasu Mathias Lécuyer 62 33 0 29 Jun 2021
PATE-AAE: Incorporating Adversarial Autoencoder into Private Aggregation of Teacher Ensembles for Spoken Command Classification Chao-Han Huck Yang Sabato Marco Siniscalchi Chin-Hui Lee 132 22 0 02 Apr 2021
High-Dimensional Differentially-Private EM Algorithm: Methods and Near-Optimal Statistical Guarantees Zhe Zhang Linjun Zhang FedML 83 3 0 01 Apr 2021
DDUO: General-Purpose Dynamic Analysis for Differential Privacy Chiké Abuah Alex Silence David Darais Joseph P. Near 70 12 0 16 Mar 2021
Dopamine: Differentially Private Federated Learning on Medical Data Mohammad Malekzadeh Burak Hasircioglu N. Mital K. Katarya M. E. Ozfatura Deniz Gündüz OOD FedML 105 51 0 27 Jan 2021
The Limits of Differential Privacy (and its Misuse in Data Release and Machine Learning) J. Domingo-Ferrer David Sánchez Alberto Blanco-Justicia 116 109 0 04 Nov 2020
Privacy-Preserving Bandits Mohammad Malekzadeh D. Athanasakis Hamed Haddadi B. Livshits 131 18 0 10 Sep 2019