LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale

14 February 2020

Papers citing "LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale"

48 / 48 papers shown

Title
But Can You Use It? Design Recommendations for Differentially Private Interactive Systems Liudas Panavas Joshua Snoke Erika Tyagi C. Bowen Aaron R. Williams 77 0 0 16 Dec 2024
Dimension-free Private Mean Estimation for Anisotropic Distributions Yuval Dagan Michael I. Jordan Xuelin Yang Lydia Zakynthinou Nikita Zhivotovskiy 39 2 0 01 Nov 2024
On the Use of Proxies in Political Ad Targeting Piotr Sapiezynski Levi Kaplan A. Mislove Aleksandra Korolova 35 2 0 18 Oct 2024
A Statistical Viewpoint on Differential Privacy: Hypothesis Testing, Representation and Blackwell's Theorem Weijie J. Su 31 1 0 14 Sep 2024
On Computing Pairwise Statistics with Local Differential Privacy Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi Adam Sealfon FedML 29 2 0 24 Jun 2024
Advances in Differential Privacy and Differentially Private Machine Learning Saswat Das Subhankar Mishra 22 3 0 06 Apr 2024
Private Count Release: A Simple and Scalable Approach for Private Data Analytics Ryan Rogers 29 0 0 08 Mar 2024
Differentially Private Fair Binary Classifications Hrad Ghoukasian S. Asoodeh FaML 32 1 0 23 Feb 2024
Mean estimation in the add-remove model of differential privacy Alex Kulesza A. Suresh Yuyan Wang 24 3 0 11 Dec 2023
Scaling Up Differentially Private LASSO Regularized Logistic Regression via Faster Frank-Wolfe Iterations Edward Raff Amol Khanna Fred Lu 12 6 0 30 Oct 2023
Some Constructions of Private, Efficient, and Optimal $K$ -Norm and Elliptic Gaussian Noise Matthew Joseph Alexander Yu 19 2 0 27 Sep 2023
A Unifying Privacy Analysis Framework for Unknown Domain Algorithms in Differential Privacy Ryan Rogers FedML 22 1 0 17 Sep 2023
Incompatibilities Between Current Practices in Statistical Data Analysis and Differential Privacy Lorin Sweeney C. Bowen Graham Healy Andrés F. Barrientos 13 3 0 16 Aug 2023
Samplable Anonymous Aggregation for Private Federated Data Analysis Kunal Talwar Shan Wang Audra McMillan Vojta Jina Vitaly Feldman ... Congzheng Song Karl Tarbe Sebastian Vogt L. Winstrom Shundong Zhou FedML 32 13 0 27 Jul 2023
Turbo: Effective Caching in Differentially-Private Databases Kelly Kostopoulou Pierre Tholoniat Asaf Cidon Roxana Geambasu Mathias Lécuyer 18 1 0 28 Jun 2023
Differentially Private Distributed Estimation and Learning Marios Papachristou M. Amin Rahimian FedML 13 2 0 28 Jun 2023
You Don't Need Robust Machine Learning to Manage Adversarial Attack Risks Edward Raff M. Benaroch Andrew L. Farris AAML 22 2 0 16 Jun 2023
Coincidental Generation Jordan W. Suchow Necdet Gurkan 25 0 0 03 Apr 2023
Multi-Task Differential Privacy Under Distribution Skew Walid Krichene Prateek Jain Shuang Song Mukund Sundararajan Abhradeep Thakurta Li Zhang FedML 32 3 0 15 Feb 2023
From Robustness to Privacy and Back Hilal Asi Jonathan R. Ullman Lydia Zakynthinou 28 27 0 03 Feb 2023
Cohere: Managing Differential Privacy in Large Scale Systems Nicolas Küchler Emanuel Opel Hidde Lycklama Alexander Viand Anwar Hithnawi 33 4 0 20 Jan 2023
Towards Separating Computational and Statistical Differential Privacy Badih Ghazi Rahul Ilango Pritish Kamath Ravi Kumar Pasin Manurangsi 20 5 0 31 Dec 2022
Lessons Learned: Surveying the Practicality of Differential Privacy in the Industry Gonzalo Munilla Garrido Xiaoyuan Liu Florian Matthes D. Song 20 24 0 07 Nov 2022
Anonymized Histograms in Intermediate Privacy Models Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi PICV 97 1 0 27 Oct 2022
On the Risks of Collecting Multidimensional Data Under Local Differential Privacy Héber H. Arcolezi Sébastien Gambs Jean-François Couchot C. Palamidessi 21 12 0 04 Sep 2022
Faster Privacy Accounting via Evolving Discretization Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi 57 14 0 10 Jul 2022
Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss Jason M. Altschuler Kunal Talwar FedML 15 57 0 27 May 2022
Differential Privacy: What is all the noise about? Roxana Dánger Mercaderes 32 3 0 19 May 2022
Differentially Private Multivariate Time Series Forecasting of Aggregated Human Mobility With Deep Learning: Input or Gradient Perturbation? Héber H. Arcolezi Jean-François Couchot Denis Renaud Bechara al Bouna X. Xiao AI4TS 28 5 0 01 May 2022
HDPView: Differentially Private Materialized View for Exploring High Dimensional Relational Data Fumiyuki Kato Tsubasa Takahashi Shun Takagi Yang Cao Seng Pei Liew Masatoshi Yoshikawa 19 6 0 14 Mar 2022
Information Design for Differential Privacy Ian M. Schmutte Nathan Yoder 12 2 0 11 Feb 2022
Plume: Differential Privacy at Scale Kareem Amin Jennifer Gillenwater Matthew Joseph Alex Kulesza Sergei Vassilvitskii 15 9 0 27 Jan 2022
Optimum Noise Mechanism for Differentially Private Queries in Discrete Finite Sets Sachin Kadam Anna Scaglione Nikhil Ravi S. Peisert B. Lunghino Aram Shumavon 11 0 0 23 Nov 2021
Improving the utility of locally differentially private protocols for longitudinal and multidimensional frequency estimates Héber H. Arcolezi Jean-François Couchot Bechara al Bouna X. Xiao 15 29 0 08 Nov 2021
Multivariate Mean Comparison under Differential Privacy Martin Dunsche T. Kutta Holger Dette 31 3 0 15 Oct 2021
Random Sampling Plus Fake Data: Multidimensional Frequency Estimates With Local Differential Privacy Héber H. Arcolezi Jean-François Couchot Bechara al Bouna Xiaokui Xiao 20 27 0 15 Sep 2021
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation Gavin Brown Marco Gaboardi Adam D. Smith Jonathan R. Ullman Lydia Zakynthinou FedML 28 48 0 24 Jun 2021
Decision Making with Differential Privacy under a Fairness Lens Ferdinando Fioretto Cuong Tran Pascal Van Hentenryck 16 45 0 16 May 2021
U.S. Broadband Coverage Data Set: A Differentially Private Data Release Mayana Pereira Allen Kim Joshua Allen Kevin White J. L. Ferres Rahul Dodhia 14 12 0 24 Mar 2021
A Central Limit Theorem for Differentially Private Query Answering Jinshuo Dong Weijie J. Su Linjun Zhang 31 15 0 15 Mar 2021
PrivSyn: Differentially Private Data Synthesis Zhikun Zhang Tianhao Wang Ninghui Li Jean Honorio Michael Backes Shibo He Jiming Chen Yang Zhang SyDa 11 64 0 30 Dec 2020
Adversarial Manifold Estimation Eddie Aamari Alexander Knop 15 2 0 09 Nov 2020
A Members First Approach to Enabling LinkedIn's Labor Market Insights at Scale Ryan M. Rogers Adrian Rivera Cardoso Koray Mancuhan Akash Kaura Nikhil T. Gahlawat Neha Jain Paul Ko P. Ahammad 19 11 0 27 Oct 2020
Privacy Amplification via Random Check-Ins Borja Balle Peter Kairouz H. B. McMahan Om Thakkar Abhradeep Thakurta FedML 22 72 0 13 Jul 2020
Understanding Unintended Memorization in Federated Learning Om Thakkar Swaroop Indra Ramaswamy Rajiv Mathews Franccoise Beaufays FedML 14 45 0 12 Jun 2020
Bounding, Concentrating, and Truncating: Unifying Privacy Loss Composition for Data Analytics Mark Cesar Ryan M. Rogers 9 3 0 15 Apr 2020
SoK: Differential Privacies Damien Desfontaines Balázs Pejó 28 121 0 04 Jun 2019
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 141 420 0 29 Nov 2018