DIMACS/Northeast Big Data Hub Workshop on Overcoming Barriers to Data Sharing including Privacy and Fairness

October 23 - 24, 2017
DIMACS Center, CoRE Building, Rutgers University

Organizing Committee:

John Abowd, U.S. Census Bureau and Cornell University

René Bastón, Columbia University

Tal Rabin, IBM

Adam Smith, Boston University

Salil Vadhan, Harvard University

Rebecca Wright, Rutgers University

Workshop email: Barriers_workshop at email.rutgers.edu

Slides:

• Jeremiah Blocki, Purdue University
  Releasing a Differentially Private Password Frequency Corpus from 70 Million Yahoo! Passwords

• Chris Clifton, Purdue University
  Parallel Composition Revisited

• Henry Corrigan-Gibbs, Stanford University
  Prio: Private, Robust, and Efficient Computation of Aggregate Statistics

• Marco Gaboardi, University at Buffalo
  Formal Verification of Differentially Private Mechanisms

• Philip Leclerc, Stephen Clark, William Sexton, US Census Bureau
  2020 Decennial Census: Formal Privacy Implementation Update

• Ashwin Machanavajjhala, Duke University
  DP & Relational Databases: A case study on Census Data

• Brendan McMahan, Google
  Guarding user Privacy with Federated Learning and Differential Privacy

• Joseph Near, UC Berkeley
  Towards Practical Differential Privacy for SQL Queries

• Mayank Varia, Boston University
  Experieces Implementing Usable MPC for Social Good

• Alexandra Wood, Harvard University
  Bridging Privacy Definitions: Differential Privacy and Privacy Concepts from Law and Policy

• Rebecca Wright, Rutgers University
  Jana: Secure Computation with Differential Privacy, and Applications

Workshop Index

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