Keyword Search
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CC = Colorado Convention Center H = Hyatt Regency Denver at Colorado Convention Center
* = applied session ! = JSM meeting theme
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Keyword Search Criteria: Privacy returned 22 record(s)
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Tuesday, 07/30/2019
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Synthetic Data as an Alternative to PUMS: Challenges, Successes, and Issues
Katherine J Thompson, U.S. Census Bureau
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Bayesian Pseudo Posterior Synthesis for Data Privacy Protection
Jingchen Hu, Vassar College; Terrance Savitsky, Bureau of Labor Statistics; Matthew Williams, National Science Foundation
9:15 AM
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PMSE Mechanism: Differentially Private Synthetic Data with Maximal Distributional Similarity
Joshua Snoke, RAND Corporation; Aleksandra Slavkovic, Penn State University
9:35 AM
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Balancing Privacy and Precision: Disclosure Control Methods in Government Surveys
Ellen Galantucci, Bureau of Labor Statistics
10:50 AM
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Wednesday, 07/31/2019
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A Bayesian Hierarchical Model for Generating Fully Synthetic Point Process Data
Adam Walder
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Statistical Approaches to Tackling Data Privacy
Evercita Cuevas Eugenio, Sandia National Laboratory; Fang Liu, University of Notre Dame
8:35 AM
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Census Barriers Attitudes and Motivators Study: a Case Study in Differential Privacy at the U.S. Census Bureau
Caleb Floyd, U.S. Census Bureau; Rolondo RodrÃguez, U.S. Census Bureau
8:35 AM
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Rationing Out Privacy-Loss: Proportional Budget Expenditure in the 2020 Decennial Census Disclosure Avoidance System
William Sexton, U.S. Census Bureau
8:55 AM
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Ensuring Output: Complex Constraints and Feasible Microdata Under Differential Privacy
Philip Leclerc, US Census Bureau
9:15 AM
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Estimating the Variance of Complex Differentially Private Algorithms
Robert Ashmead, Ohio Colleges of Medicine Government Resource Center
9:35 AM
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A Bayesian Hierarchical Model for Generating Fully Synthetic Point Process Data
Adam Walder
9:40 AM
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Protecting Privacy of Household Panel Data
Shaobo Li, University of Kansas; Matthew Schneider, Drexel University; Yan Yu, University of Cincinnati; Sachin Gupta, Cornell University
9:50 AM
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Formal Privacy: Making an Impact at Large Organizations
Simson Garfinkel, US Census Bureau; Ilya Mironov, Google; Juan Lavista Ferres, Microsoft; Shiva Kasiviswanathan, Amazon
10:35 AM
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LOWERING the CRAMER-RAO LOWER BOUND of VARIANCE in RANDOMIZED RESPONSE SAMPLING
Tonghui Xu, Texas A&M University -kingsville; Stephen Sedory, Texas A & M University-Kingsville; Sarjinder Singh, Texas A&M University-Kingsville
2:50 PM
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A Review and Update of the Two-Decks of Cards Method in Randomized Response Sampling
Augustus Jayaraj, Cornell University; Oluseun Odumade, Deloitte & Touche LLP; Sarjinder Singh, Texas A&M University-Kingsville
3:20 PM
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Thursday, 08/01/2019
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Optimal Inference Under Formal Privacy for Binomial Data
Aleksandra Slavkovic, Penn State University; Jordan Awan, Penn State University
10:55 AM
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Privacy-Preserving Technologies Meet Machine Learning
Jeannette Wing, Columbia University, Data Science Institute
11:00 AM
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Privacy-Preserving Prediction
Cynthia Dwork, Harvard University; Vitaly Feldman, Google
11:25 AM
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Differential Privacy and Synthetic Data for Disclosure Control
Barrientos Felipe Andres, Duke University; Jerry Reiter, Duke University; Tom Balmat, Duke University
11:35 AM
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