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The Limits of Pan Privacy and Shuffle Privacy for Learning and Estimation

Sep 23, 2020
Albert Cheu, Jonathan Ullman


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Auditing Differentially Private Machine Learning: How Private is Private SGD?

Jun 13, 2020
Matthew Jagielski, Jonathan Ullman, Alina Oprea


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CoinPress: Practical Private Mean and Covariance Estimation

Jun 11, 2020
Sourav Biswas, Yihe Dong, Gautam Kamath, Jonathan Ullman

* Code is available at https://github.com/twistedcubic/coin-press 

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A Primer on Private Statistics

Apr 30, 2020
Gautam Kamath, Jonathan Ullman

* 20 pages. Comments welcome 

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Private Query Release Assisted by Public Data

Apr 23, 2020
Raef Bassily, Albert Cheu, Shay Moran, Aleksandar Nikolov, Jonathan Ullman, Zhiwei Steven Wu


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Private Mean Estimation of Heavy-Tailed Distributions

Feb 21, 2020
Gautam Kamath, Vikrant Singhal, Jonathan Ullman


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The Power of Factorization Mechanisms in Local and Central Differential Privacy

Nov 19, 2019
Alexander Edmonds, Aleksandar Nikolov, Jonathan Ullman


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Differentially Private Algorithms for Learning Mixtures of Separated Gaussians

Oct 15, 2019
Gautam Kamath, Or Sheffet, Vikrant Singhal, Jonathan Ullman

* To appear in NeurIPS 2019 

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Private Identity Testing for High-Dimensional Distributions

May 28, 2019
Clément L. Canonne, Gautam Kamath, Audra McMillan, Jonathan Ullman, Lydia Zakynthinou


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Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy

May 24, 2019
Adam Sealfon, Jonathan Ullman


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Efficient Private Algorithms for Learning Halfspaces

Feb 24, 2019
Huy L. Nguyen, Jonathan Ullman, Lydia Zakynthinou

* 21 pages 

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Differentially Private Fair Learning

Dec 06, 2018
Matthew Jagielski, Michael Kearns, Jieming Mao, Alina Oprea, Aaron Roth, Saeed Sharifi-Malvajerdi, Jonathan Ullman


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The Structure of Optimal Private Tests for Simple Hypotheses

Nov 27, 2018
Clément L. Canonne, Gautam Kamath, Audra McMillan, Adam Smith, Jonathan Ullman


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Privately Learning High-Dimensional Distributions

Sep 18, 2018
Gautam Kamath, Jerry Li, Vikrant Singhal, Jonathan Ullman


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The Limits of Post-Selection Generalization

Jun 15, 2018
Kobbi Nissim, Adam Smith, Thomas Steinke, Uri Stemmer, Jonathan Ullman


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Local Differential Privacy for Evolving Data

May 22, 2018
Matthew Joseph, Aaron Roth, Jonathan Ullman, Bo Waggoner


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Tight Lower Bounds for Locally Differentially Private Selection

Feb 07, 2018
Jonathan Ullman


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Skyline Identification in Multi-Armed Bandits

Jan 09, 2018
Albert Cheu, Ravi Sundaram, Jonathan Ullman

* 18 pages, 2 Figures; an ALT'18/ISIT'18 submission 

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Multidimensional Dynamic Pricing for Welfare Maximization

Jun 10, 2017
Aaron Roth, Aleksandrs Slivkins, Jonathan Ullman, Zhiwei Steven Wu


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Make Up Your Mind: The Price of Online Queries in Differential Privacy

Apr 15, 2016
Mark Bun, Thomas Steinke, Jonathan Ullman


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Watch and Learn: Optimizing from Revealed Preferences Feedback

Nov 18, 2015
Aaron Roth, Jonathan Ullman, Zhiwei Steven Wu


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More General Queries and Less Generalization Error in Adaptive Data Analysis

Nov 10, 2015
Raef Bassily, Adam Smith, Thomas Steinke, Jonathan Ullman

* This paper was merged with another manuscript and is now subsumed by arXiv:1511.02513 

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Algorithmic Stability for Adaptive Data Analysis

Nov 08, 2015
Raef Bassily, Kobbi Nissim, Adam Smith, Thomas Steinke, Uri Stemmer, Jonathan Ullman

* This work unifies and subsumes the two arXiv manuscripts arXiv:1503.04843 and arXiv:1504.05800 

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Interactive Fingerprinting Codes and the Hardness of Preventing False Discovery

Feb 20, 2015
Thomas Steinke, Jonathan Ullman


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Between Pure and Approximate Differential Privacy

Jan 24, 2015
Thomas Steinke, Jonathan Ullman


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Preventing False Discovery in Interactive Data Analysis is Hard

Aug 06, 2014
Moritz Hardt, Jonathan Ullman


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Privately Solving Linear Programs

May 08, 2014
Justin Hsu, Aaron Roth, Tim Roughgarden, Jonathan Ullman


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Privately Releasing Conjunctions and the Statistical Query Barrier

Oct 27, 2011
Anupam Gupta, Moritz Hardt, Aaron Roth, Jonathan Ullman


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