Event Calendar

Jul
31
Sun
2016
JSM Session: Employer List Linking: Methods, Implementation, and Usage of Probabilistic Matches for Enhancing Workforce Statistics @ McCormick Conference Center
Jul 31 @ 14:00 – 15:30
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Lars Vilhuber chairs session at JSM which includes multiple papers with NCRN contribution (presenter bolded, NCRN participants in red italics):

2:05 PM
Robustness of Employer List Linking to Methodological Variation — Mark J. Kutzbach, U.S. Census Bureau ; Graton Gathright, U.S. Census Bureau ; Andrew Green, U.S. Census Bureau/Cornell University ; Kristin McCue, U.S. Census Bureau ; Holly Monti, U.S. Census Bureau ; Ann Rodgers, University of Michigan ; Lars Vilhuber, Cornell University ; Nada Wasi, University of Michigan ; Christopher Wignall, Amazon.com

2:25 PM
Two Perspectives on Commuting and Workplace: A Microdata Comparison of Home-to-Work Flows Across Linked Survey and Administrative Files— Andrew Green, Cornell University/U.S. Census Bureau ; Mark J. Kutzbach, U.S. Census Bureau ; Lars Vilhuber, Cornell University

2:45 PM
Developing Job Linkages for the Health and Retirement Study — Kristin McCue, U.S. Census Bureau ; John M. Abowd, U.S. Census Bureau/Cornell University ; Margaret Levenstein, University of Michigan ; Matthew Shapiro, University of Michigan ; Ann Rodgers, University of Michigan ; Nada Wasi, University of Michigan ; Dhiren Patki, University of Michigan

Aug
1
Mon
2016
JSM Session: Advances in Statistical Methods for Dissemination and Analysis of Official Statistics @ McCormick Conference Center
Aug 1 @ 14:00 – 15:50
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John M. Abowd (former NCRN-Cornell PI) and other NCRN PIs present:

2:05 PM
An Integrated Approach to Providing Access to Confidential Social Science Data — Jerome Reiter, Duke University

2:30 PM
The Challenge of Reproducible Science and Privacy Protection for Statistical Agencies — John M. Abowd, U.S. Census Bureau/Cornell University

2:55 PM
Spatio-Temporal Change of Support with Application to American Community Survey Multi-Year Period Estimates — Scott H. Holan, University of Missouri ; Jonathan R. Bradley, University of Missouri ; Christopher Wikle, University of Missouri

JSM Session: Statistical Foundations of Data Privacy @ McCormick Conference Center
Aug 1 @ 14:00 – 15:50
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Lars Vilhuber chairs a session organized by the Committee on Privacy and Confidentiality and Aleksandra Slavkovic, Penn State University:

2:05 PM
Connections Between Privacy Definitions and Arbitrage-Free Pricing Functions — Daniel Kifer, Penn State University

2:25 PM
Differentially Private Statistical Inference and Hypothesis Testing — Vishesh Karwa, Carnegie Mellon University

2:45 PM
Learning with Differential Privacy: Stability, Learnability, and the Sufficiency and Necessity of ERM Principle — Yu-Xiang Wang, Carnegie Mellon University ; Jing Lei, Carnegie Mellon University ; Stephen E. Fienberg, Carnegie Mellon University

3:05 PM
Performance Bounds for Graphical Record Linkage: Can record linkage bounds provide guidance for private synthetic data release? — Rebecca Steorts, Duke University ; Matt Barnes, Carnegie Mellon University ; Willie Neisweigner, Carnegie Mellon University

3:25 PM
Discussant: Adam Smith, Penn State University

Nov
30
Wed
2016
Lars Vilhuber: “Disclosure Limitation and Confidentiality Protection in Linked Data” @ Centre interuniversitaire de recherche en analyse des organisations
Nov 30 @ 08:30 – 14:00
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Lars Vilhuber speaks about “Disclosure Limitation and Confidentiality Protection in Linked Data” at the Center for Interuniversity Research and Analysis of Organizations‘s conference on “Facilitate the access to Quebec data: How and to what ends?” The conference is jointly organized with the Quebec inter-University Centre for Social Statistics (QICSS). The presentation relies on joint work with John M. Abowd and Ian M. Schmutte.

[Presentation]

Jun
8
Thu
2017
Workshop: Herramientas prácticas para la apertura y uso seguro de microdatos de firmas @ Offices of CAF in Argentina
Jun 8 all-day
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Vilhuber participates in a workshop by Latin American government and research analysts and data providers, regarding the potential secure use of firm microdata.