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Private Pareto Optimal Exchange

Published: 23 October 2018 Publication History

Abstract

We consider the problem of implementing an individually rational, asymptotically Pareto optimal allocation in a barter-exchange economy where agents are endowed with goods and preferences over the goods of others, but may not use money as a medium of exchange. Because one of the most important instantiations of such economies is kidney exchange—where the “input” to the problem consists of sensitive patient medical records—we ask to what extent such exchanges can be carried out while providing formal privacy guarantees to the participants. We show that individually rational allocations cannot achieve any non-trivial approximation to Pareto optimality if carried out under the constraint of differential privacy—or even the relaxation of joint-differential privacy, under which it is known that asymptotically optimal allocations can be computed in two sided markets (Hsu et al. STOC 2014). We therefore consider a further relaxation that we call marginal-differential privacy—which promises, informally, that the privacy of every agent i is protected from every other agent ji so long as j does not collude or share allocation information with other agents. We show that under marginal differential privacy, it is possible to compute an individually rational and asymptotically Pareto optimal allocation in such exchange economies.

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Cited By

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  • (2023)Differentially private condorcet votingProceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v37i5.25714(5755-5763)Online publication date: 7-Feb-2023
  • (2021)More than PrivacyACM Computing Surveys10.1145/346077154:7(1-37)Online publication date: 18-Jul-2021

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Published In

cover image ACM Transactions on Economics and Computation
ACM Transactions on Economics and Computation  Volume 6, Issue 3-4
Special Issue on EC'15
November 2018
249 pages
ISSN:2167-8375
EISSN:2167-8383
DOI:10.1145/3281297
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 October 2018
Accepted: 01 May 2017
Revised: 01 January 2017
Received: 01 January 2016
Published in TEAC Volume 6, Issue 3-4

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Author Tags

  1. Mechanism design without money
  2. differential privacy
  3. exchange markets

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  • Google Focused Research Award

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Cited By

View all
  • (2023)Differentially private condorcet votingProceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v37i5.25714(5755-5763)Online publication date: 7-Feb-2023
  • (2021)More than PrivacyACM Computing Surveys10.1145/346077154:7(1-37)Online publication date: 18-Jul-2021

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