An Analysis of the Deployment of Models Trained on Private Tabular Synthetic Data: Unexpected Surprises

15 June 2021

Papers citing "An Analysis of the Deployment of Models Trained on Private Tabular Synthetic Data: Unexpected Surprises"

9 / 9 papers shown

Title
FFPDG: Fast, Fair and Private Data Generation Weijie Xu Jinjin Zhao Francis Iannacci Bo Wang 53 11 0 30 Jun 2023
U.S. Broadband Coverage Data Set: A Differentially Private Data Release Mayana Pereira Allen Kim Joshua Allen Kevin White J. L. Ferres Rahul Dodhia 41 12 0 24 Mar 2021
Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary Jean-Francois Rajotte Soumendu Sundar Mukherjee Caleb Robinson Anthony Ortiz Christopher West J. L. Ferres R. Ng FedML MedIm 147 41 0 18 Jan 2021
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 277 494 0 31 Dec 2020
Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning Joseph Paul Cohen Lan Dao Paul Morrison Karsten Roth Yoshua Bengio ... A. Abbasi M. Hoshmand-Kochi Marzyeh Ghassemi Haifang Li T. Duong 56 224 0 24 May 2020
Google COVID-19 Community Mobility Reports: Anonymization Process Description (version 1.1) A. Aktay S. Bavadekar Gwen Cossoul John Davis Damien Desfontaines ... Swapnil Vispute Mia Vu G. Wellenius Brian Williams Royce J. Wilson 27 545 0 08 Apr 2020
Modeling Tabular data using Conditional GAN Lei Xu Maria Skoularidou Alfredo Cuesta-Infante K. Veeramachaneni CML MU SyDa GAN 100 1,246 0 01 Jul 2019
ProPublica's COMPAS Data Revisited M. Barenstein FaML 42 51 0 11 Jun 2019
Differential Privacy Has Disparate Impact on Model Accuracy Eugene Bagdasaryan Vitaly Shmatikov 129 480 0 28 May 2019