Aaron Roth

Publications
  1. Rawlsian Fairness for Machine Learning. Joint with Matthew Joseph, Jamie Morgenstern, Michael Kearns, and Seth Neel. Manuscript.
  2. Meritocratic Fairness for Cross-Population Selection. Joint with Michael Kearns and Steven Wu. To appear in ICML 2017.
  3. Fairness in Reinforcement Learning. Joint with Shahin Jabbari, Matthew Joseph, Jamie Morgenstern, and Michael Kearns. To appear in ICML 2017.
  4. A Framework for Adaptive Differential Privacy. Joint with Daniel Winograd-Cort, Andreas Haeberlen, and Benjamin Pierce. To appear in ICFP 2017.
  5. Fairness Incentives for Myopic Agents. Joint with Sampath Kannan, Michael Kearns, Jamie Morgenstern, Mallesh Pai, Rakesh Vohra, and Steven Wu. To appear in EC 2017.
  6. Multidimensional Dynamic Pricing for Welfare Maximization. Joint with Alex Slivkins, Jon Ullman and Steven Wu. To appear in EC 2017.
  7. Guilt Free Data Reuse. Joint work with Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, and Omer Reingold. In Communications of the ACM. April 2017.
  8. Computer-aided verification in mechanism design. Joint with Gilles Barthe, Marco Gaboardi, Emilio Jesus Gallego Arias, Justin Hsu, and Pierre-Yves Strub. In the proceedings of WINE 2016.
  9. Privacy Odometers and Filters: Pay-as-you-Go Composition. Joint with Ryan Rogers, Jon Ullman, and Salil Vadhan. In the proceedings of NIPS 2016.
  10. Fairness in Learning: Classic and Contextual Bandits. Joint with Matthew Joseph, Jamie Morgenstern, and Michael Kearns. In the proceedings of NIPS 2016.
  11. Robust Mediators in Large Games. Joint with Michael Kearns, Mallesh Pai, Ryan Rogers, and Jon Ullman. Manuscript. (This paper is a merge of two papers below, and subsumes both "Mechanism Design in Large Games: Incentives and Privacy" which appeared in ITCS 2014, and "Asymptotically Truthful Equilibrium Selection" which appeared in EC 2014).
  12. Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs. Joint work with Shahin Jabbari, Ryan Rogers, and Steven Wu. In the proceedings of NIPS 2016.
  13. Max-Information, Differential Privacy, and Post-Selection Hypothesis Testing. Joint with Ryan Rogers, Adam Smith, and Om Thakkar. In the proceedings of FOCS 2016.
  14. The Strange Case of Privacy in Equilibrium Models. Joint work with Rachel Cummings, Katrina Ligett, and Mallesh Pai. In the proceedings of EC 2016.
  15. An Anti-Folk Theorem for Large Repeated Games with Imperfect Monitoring. Joint with Mallesh Pai and Jon Ullman. Transactions on Economics and Computation, 2016.
  16. Adaptive Learning with Robust Generalization Guarantees. Joint with Rachel Cummings, Katrina Ligett, Kobbi Nissim, and Steven Wu. In the proceedings of COLT 2016.
  17. Tight Policy Regret Bounds for Monotone Bandits. Joint work With Hoda Heidari and Michael Kearns. In the proceedings of IJCAI 2016.
  18. Do Prices Coordinate Markets?. Joint work with Justin Hsu, Jamie Morgenstern, Ryan Rogers, and Rakesh Vohra. In the proceedings of STOC 2016.
  19. Watch and Learn: Optimizing from Revealed Preferences Feedback. Joint with Jon Ullman and Steven Wu. In the proceedings of STOC 2016.
  20. Private Algorithms for the Protected in Social Network Search. Joint with Michael Kearns, Steven Wu, and Grigory Yaroslavtsev. In Proceedings of the National Academy of Sciences (PNAS), January 2016.
  21. Coordination Complexity: Small Information Coordinating Large Populations. Joint with Rachel Cummings, Katrina Ligett, Jaikumar Radhakrishnan and Steven Wu. In the proceedings of in ITCS 2016.
  22. Jointly Private Convex Programming. Joint work with Justin Hsu, Zhiyi Huang, and Steven Wu. In the proceedings of SODA 2016.
  23. Privacy and Truthful Equilibrium Selection for Aggregative Games. Joint with Rachel Cummings, Michael Kearns, and Steven Wu. In the proceedings of WINE 2015.
  24. Generalization in Adaptive Data Analysis and Holdout Reuse. Joint work with Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, and Omer Reingold. In the proceedings of NIPS 2015.
  25. The Reusable Holdout: Preserving Validity in Adaptive Data Analysis Joint work with Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, and Omer Reingold. In Science, August 7 2015.
  26. Inducing Approximately Optimal Flow Using Truthful Mediators. Joint work with Ryan Rogers, Jonathan Ullman, and Steven Wu. In the proceedings of EC 2015.
  27. Private Pareto Optimal Exchange. Joint with Sampath Kannan, Jamie Morgenstern, and Ryan Rogers. In the proceedings of EC 2015.
  28. Preserving Statistical Validity in Adaptive Data Analysis. Joint work with Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, and Omer Reingold. In the proceedings of STOC 2015.
  29. Online Learning and Profit Maximization from Revealed Preferences. Joint with Kareem Amin, Rachel Cummings, Lili Dworkin, and Michael Kearns. In the proceedings of AAAI 2015.
  30. Accuracy for Sale: Aggregating Data with a Variance Constraint. Joint with Rachel Cummings, Katrina Ligett, Steven Wu, and Juba Ziani. In the proceedings of ITCS 2015.
  31. Higher-Order Approximate Relational Refinement Types for Mechanism Design and Differential Privacy. Joint with Gilles Barthe, Marco Gaboardi, Emilio Jesús Gallego Arias, Justin Hsu, and Pierre-Yves Strub. In the proceedings of POPL 2015.
  32. Approximately Stable, School Optimal, and Student-Truthful Many-to-One Matchings (via Differential Privacy). Joint with Sampath Kannan, Jamie Morgenstern, and Steven Wu. In the proceedings of SODA 2015.
  33. The Algorithmic Foundations of Differential Privacy. Joint with Cynthia Dwork. Foundations and Trends in Theoretical Computer Science, NOW Publishers. 2014.
  34. Dual Query: Practical Private Query Release for High Dimensional Data. Joint work with Marco Gaboradi, Emilio Jesús Gallego Arias, Justin Hsu, and Steven Wu. In the proceedings of ICML 2014.
  35. Differential Privacy: An Economic Method for Choosing Epsilon. Joint with Justin Hsu, Marco Gaboardi, Andreas Haeberlen, Sanjeev Khanna, Arjun Narayan, and Benjamin C. Pierce. In the proceedings of CSF 2014.
  36. Privately Solving Linear Programs. Joint with Justin Hsu, Tim Roughgarden, and Jon Ullman. In the proceedings of ICALP 2014.
  37. Buying Private Data without Verification. Joint work with Arpita Ghosh, Katrina Ligett, and Grant Schoenebeck. In the proceedings of EC 2014.
  38. Asymptotically Truthful Equilibrium Selection in Large Congestion Games. Joint work with Ryan Rogers. In the proceedings of EC 2014.
  39. Bounds for the Query Complexity of Approximate Equilibria. Joint work with Paul Goldberg In the proceedings of EC 2014.
    Invited to a special issue of Transactions on Economics and Computation (TEAC) 2015.
  40. Private Matchings and Allocations. Joint work with Justin Hsu, Zhiyi Huang, Tim Roughgarden, and Steven Wu. In the proceedings of STOC 2014.
  41. Mechanism Design in Large Games: Incentives and Privacy. Joint with Michael Kearns, Mallesh Pai, and Jon Ullman. In the proceedings of ITCS 2014.
  42. Constrained Signaling in Auction Design. Joint work with Shaddin Dughmi and Nicole Immorlica. In the proceedings of SODA 2014.
  43. Exploiting Metric Structure for Efficient Private Query Release. Joint work with Zhiyi Huang. In the proceedings of SODA 2014.
  44. Beyond Worst-Case Analysis in Private Singular Vector Computation. Joint with Moritz Hardt. In the proceedings of STOC 2013.
  45. Differential Privacy for the Analyst via Private Equilibrium Computation. Joint with Justin Hsu and Jon Ullman. In the proceedings of STOC 2013.
  46. Fast Private Algorithms for Sparse Queries. Joint with Avrim Blum. In the proceedings of RANDOM 2013.
  47. Privacy and Mechanism Design. Joint with Mallesh Pai. SIGecom Exchanges, 2013.
  48. Efficiently Learning from Revealed Preference. Joint with Morteza Zadimoghaddam. In the proceedings of WINE 2012.
  49. Conducting Truthful Surveys, Cheaply. Joint with Grant Schoenebeck. In the proceedings of EC 2012.
  50. Distributed Private Heavy Hitters. Joint with Justin Hsu and Sanjeev Khanna. In the proceedings of ICALP 2012.
  51. Beating Randomized Response on Incoherent Matrices. Joint with Moritz Hardt. In the proceedings of STOC 2012.
  52. Iterative Constructions and Private Data Release. Joint with Anupam Gupta and Jonathan Ullman. In the proceedings of TCC 2012.
  53. Privately Releasing Conjunctions and the Statistical Query Barrier. Joint with Anupam Gupta, Moritz Hardt, and Jonathan Ullman. In the proceedings of STOC 2011.
    Full version appears in SIAM Journal on Computing (SICOMP) 2013.
  54. Take it or leave it: Running a Survey when Privacy Comes at a Cost. Joint with Katrina Ligett. In the Proceedings of WINE 2012.
  55. Selling Privacy at Auction. Joint work with Arpita Ghosh. In the proceedings of EC 2011.
    Invited to a special issue of Games and Economic Behavior (GEB) 2013.
  56. New Algorithms for Preserving Differential Privacy. PhD Thesis.
  57. Interactive Privacy via the Median Mechanism. Joint with Tim Roughgarden. In the proceedings of STOC 2010.
  58. Constrained Non-Monotone Submodular Maximization: Offline and Secretary Algorithms. Joint with Anupam Gupta, Grant Schoenebeck, and Kunal Talwar. In the Proceedings of WINE 2010.
  59. Differentially Private Combinatorial Optimization. Joint with Anupam Gupta, Katrina Ligett, Frank McSherry, and Kunal Talwar. In the Proceedings of  SODA 2010.
  60. Auctions with Online Supply. Joint with Moshe Babaioff and Liad Blumrosen. In the Proceedings Of EC 2010.
    Full version appears in Games and Economic Behavior, 2015.
  61. On the Equilibria of Alternating Move Games. Joint with Maria Florina Balcan, Adam Kalai, and Yishay Mansour. In the Proceedings of SODA 2010.
  62. Differential Privacy and the Fat-Shattering Dimension of Linear Queries. In the Proceedings of RANDOM 2010.
  63. The Power of Fair Pricing Mechanisms. Joint with Christine Chung, Katrina Ligett, and Kirk Pruhs. In the Proceedings of LATIN 2010. (Invited to a special issue of Algorithmica)
  64. A Learning Theory Approach to Non-Interactive Database Privacy. Joint with Avrim Blum and Katrina Ligett. In the proceedings of STOC 2008: The 40th ACM Symposium on the Theory of Computing.
    Full version appears in Journal of the ACM (JACM) 2013.
  65.  The Price of Stochastic Anarchy. Joint with Christine Chung, Katrina Ligett, and Kirk Pruhs. In the proceedings of SAGT 2008: The first Annual Symposium on Algorithmic Game Theory.
  66. The Price of Malice in Linear Congestion Games. In the Proceedings of WINE 2008.
  67. Regret Minimization and the Price of Total Anarchy. Joint with Avrim Blum, MohammadTaghi Hajiaghayi, and Katrina Ligett. In the proceedings of STOC 2008: The 40th ACM Symposium on the Theory of Computing.