Jonathan R. Ullman

165 papers A* 45A 4B 5C 1Misc 3Journal 97Unranked 9

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Black-Box Privacy Attacks on Shared Representations in Multitask Learning. CoRR John Abascal, Nicolás Berrios, Alina Oprea, Jonathan R. Ullman, Adam Smith, Matthew Jagielski
2025	A	`conf`	Privacy in Metalearning and Multitask Learning: Modeling and Separations. AISTATS Maryam Aliakbarpour, Konstantina Bairaktari, Adam Smith, Marika Swanberg, Jonathan R. Ullman
2025	A*	`conf`	Private Mean Estimation with Person-Level Differential Privacy. SODA Sushant Agarwal, Gautam Kamath, Mahbod Majid, Argyris Mouzakis, Rose Silver, Jonathan R. Ullman
2025	J	`jnl`	The Sample Complexity of Membership Inference and Privacy Auditing. CoRR Mahdi Haghifam, Adam D. Smith, Jonathan R. Ullman
2024	A*	`conf`	Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning. ICLR Harsh Chaudhari, Giorgio Severi, Alina Oprea, Jonathan R. Ullman
2024	A	`conf`	Differentially Private Medians and Interior Points for Non-Pathological Data. ITCS Maryam Aliakbarpour, Rose Silver, Thomas Steinke, Jonathan R. Ullman
2024	A*	`conf`	How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization. ICML Andrew Lowy, Jonathan R. Ullman, Stephen J. Wright
2024	J	`jnl`	How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization. CoRR Andrew Lowy, Jonathan R. Ullman, Stephen J. Wright
2024	J	`jnl`	Investigating the Visual Utility of Differentially Private Scatterplots. IEEE Trans. Vis. Comput. Graph. Liudas Panavas, Tarik Crnovrsanin, Jane Lydia Adams, Jonathan R. Ullman, Ali Sarvghad, Melanie Tory, Cody Dunne
2024	A*	`conf`	Metalearning with Very Few Samples Per Task. COLT Maryam Aliakbarpour, Konstantina Bairaktari, Gavin Brown, Adam Smith, Nathan Srebro, Jonathan R. Ullman
2024	J	`jnl`	Privacy in Metalearning and Multitask Learning: Modeling and Separations. CoRR Maryam Aliakbarpour, Konstantina Bairaktari, Adam D. Smith, Marika Swanberg, Jonathan R. Ullman
2024	A*	`conf`	Private Geometric Median. NeurIPS Mahdi Haghifam, Thomas Steinke, Jonathan R. Ullman
2024	J	`jnl`	Private Geometric Median. CoRR Mahdi Haghifam, Thomas Steinke, Jonathan R. Ullman
2024	J	`jnl`	Private Mean Estimation with Person-Level Differential Privacy. CoRR Sushant Agarwal, Gautam Kamath, Mahbod Majid, Argyris Mouzakis, Rose Silver, Jonathan R. Ullman
2024	J	`jnl`	Program Analysis for Adaptive Data Analysis. Proc. ACM Program. Lang. Jiawen Liu, Weihao Qu, Marco Gaboardi, Deepak Garg, Jonathan R. Ullman
2024	A*	`conf`	Smooth Lower Bounds for Differentially Private Algorithms via Padding-and-Permuting Fingerprinting Codes. COLT Naty Peter, Eliad Tsfadia, Jonathan R. Ullman
2024	J	`jnl`	TMI! Finetuned Models Leak Private Information from their Pretraining Data. Proc. Priv. Enhancing Technol. John Abascal, Stanley Wu, Alina Oprea, Jonathan R. Ullman
2023	J	`jnl`	A Bias-Variance-Privacy Trilemma for Statistical Estimation. CoRR Gautam Kamath, Argyris Mouzakis, Matthew Regehr, Vikrant Singhal, Thomas Steinke, Jonathan R. Ullman
2023	J	`jnl`	Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning. CoRR Harsh Chaudhari, Giorgio Severi, Alina Oprea, Jonathan R. Ullman
2023	J	`jnl`	Differentially Private Medians and Interior Points for Non-Pathological Data. CoRR Maryam Aliakbarpour, Rose Silver, Thomas Steinke, Jonathan R. Ullman
2023	J	`jnl`	Fair and Useful Cohort Selection. Trans. Mach. Learn. Res. Konstantina Bairaktari, Paul Langton, Huy L. Nguyen, Niklas Smedemark-Margulies, Jonathan R. Ullman
2023	A*	`conf`	From Robustness to Privacy and Back. ICML Hilal Asi, Jonathan R. Ullman, Lydia Zakynthinou
2023	J	`jnl`	From Robustness to Privacy and Back. CoRR Hilal Asi, Jonathan R. Ullman, Lydia Zakynthinou
2023	J	`jnl`	How to Combine Membership-Inference Attacks on Multiple Updated Machine Learning Models. Proc. Priv. Enhancing Technol. Matthew Jagielski, Stanley Wu, Alina Oprea, Jonathan R. Ullman, Roxana Geambasu
2023	J	`jnl`	Metalearning with Very Few Samples Per Task. CoRR Maryam Aliakbarpour, Konstantina Bairaktari, Gavin Brown, Adam Smith, Jonathan R. Ullman
2023	A*	`conf`	Multitask Learning via Shared Features: Algorithms and Hardness. COLT Konstantina Bairaktari, Guy Blanc, Li-Yang Tan, Jonathan R. Ullman, Lydia Zakynthinou
2023	A*	`conf`	SNAP: Efficient Extraction of Private Properties with Poisoning. SP Harsh Chaudhari, John Abascal, Alina Oprea, Matthew Jagielski, Florian Tramèr, Jonathan R. Ullman
2023	J	`jnl`	Smooth Lower Bounds for Differentially Private Algorithms via Padding-and-Permuting Fingerprinting Codes. CoRR Naty Peter, Eliad Tsfadia, Jonathan R. Ullman
2023	J	`jnl`	TMI! Finetuned Models Leak Private Information from their Pretraining Data. CoRR John Abascal, Stanley Wu, Alina Oprea, Jonathan R. Ullman
2022	A*	`conf`	A Private and Computationally-Efficient Estimator for Unbounded Gaussians. COLT Gautam Kamath, Argyris Mouzakis, Vikrant Singhal, Thomas Steinke, Jonathan R. Ullman
2022	J	`jnl`	How to Combine Membership-Inference Attacks on Multiple Updated Models. CoRR Matthew Jagielski, Stanley Wu, Alina Oprea, Jonathan R. Ullman, Roxana Geambasu
2022	J	`jnl`	Instance-Optimal Differentially Private Estimation. CoRR Audra McMillan, Adam D. Smith, Jonathan R. Ullman
2022	J	`jnl`	Multitask Learning via Shared Features: Algorithms and Hardness. CoRR Konstantina Bairaktari, Guy Blanc, Li-Yang Tan, Jonathan R. Ullman, Lydia Zakynthinou
2022	J	`jnl`	SNAP: Efficient Extraction of Private Properties with Poisoning. CoRR Harsh Chaudhari, John Abascal, Alina Oprea, Matthew Jagielski, Florian Tramèr, Jonathan R. Ullman
2021	J	`jnl`	A Private and Computationally-Efficient Estimator for Unbounded Gaussians. CoRR Gautam Kamath, Argyris Mouzakis, Vikrant Singhal, Thomas Steinke, Jonathan R. Ullman
2021	J	`jnl`	Algorithmic Stability for Adaptive Data Analysis. SIAM J. Comput. Raef Bassily, Kobbi Nissim, Adam D. Smith, Thomas Steinke, Uri Stemmer, Jonathan R. Ullman
2021	A*	`conf`	Covariance-Aware Private Mean Estimation Without Private Covariance Estimation. NeurIPS Gavin Brown, Marco Gaboardi, Adam D. Smith, Jonathan R. Ullman, Lydia Zakynthinou
2021	J	`jnl`	Covariance-Aware Private Mean Estimation Without Private Covariance Estimation. CoRR Gavin Brown, Marco Gaboardi, Adam D. Smith, Jonathan R. Ullman, Lydia Zakynthinou
2021	J	`jnl`	Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy. J. Priv. Confidentiality Adam Sealfon, Jonathan R. Ullman
2021	A*	`conf`	Leveraging Public Data for Practical Private Query Release. ICML Terrance Liu, Giuseppe Vietri, Thomas Steinke, Jonathan R. Ullman, Zhiwei Steven Wu
2021	J	`jnl`	Leveraging Public Data for Practical Private Query Release. CoRR Terrance Liu, Giuseppe Vietri, Thomas Steinke, Jonathan R. Ullman, Zhiwei Steven Wu
2021	A*	`conf`	Manipulation Attacks in Local Differential Privacy. SP Albert Cheu, Adam D. Smith, Jonathan R. Ullman
2021	J	`jnl`	Manipulation Attacks in Local Differential Privacy. J. Priv. Confidentiality Albert Cheu, Adam D. Smith, Jonathan R. Ullman
2021	A*	`conf`	The limits of pan privacy and shuffle privacy for learning and estimation. STOC Albert Cheu, Jonathan R. Ullman
2020	J	`jnl`	A Primer on Private Statistics. CoRR Gautam Kamath, Jonathan R. Ullman
2020	A*	`conf`	Auditing Differentially Private Machine Learning: How Private is Private SGD? NeurIPS Matthew Jagielski, Jonathan R. Ullman, Alina Oprea
2020	J	`jnl`	Auditing Differentially Private Machine Learning: How Private is Private SGD? CoRR Matthew Jagielski, Jonathan R. Ullman, Alina Oprea
2020	A*	`conf`	CoinPress: Practical Private Mean and Covariance Estimation. NeurIPS Sourav Biswas, Yihe Dong, Gautam Kamath, Jonathan R. Ullman
2020	J	`jnl`	CoinPress: Practical Private Mean and Covariance Estimation. CoRR Sourav Biswas, Yihe Dong, Gautam Kamath, Jonathan R. Ullman
2020	Misc	`conf`	Differentially Private Algorithms for Learning Mixtures of Separated Gaussians. ITA Gautam Kamath, Or Sheffet, Vikrant Singhal, Jonathan R. Ullman
2020	B	`conf`	Efficient Private Algorithms for Learning Large-Margin Halfspaces. ALT Huy Le Nguyen, Jonathan R. Ullman, Lydia Zakynthinou
2020	J	`jnl`	Local Differential Privacy for Evolving Data. J. Priv. Confidentiality Matthew Joseph, Aaron Roth, Jonathan R. Ullman, Bo Waggoner
2020	J	`jnl`	Multidimensional Dynamic Pricing for Welfare Maximization. ACM Trans. Economics and Comput. Aaron Roth, Aleksandrs Slivkins, Jonathan R. Ullman, Zhiwei Steven Wu
2020	J	`jnl`	PCPs and the Hardness of Generating Synthetic Data. J. Cryptol. Jonathan R. Ullman, Salil P. Vadhan
2020	A*	`conf`	Private Identity Testing for High-Dimensional Distributions. NeurIPS Clément L. Canonne, Gautam Kamath, Audra McMillan, Jonathan R. Ullman, Lydia Zakynthinou
2020	A*	`conf`	Private Mean Estimation of Heavy-Tailed Distributions. COLT Gautam Kamath, Vikrant Singhal, Jonathan R. Ullman
2020	J	`jnl`	Private Mean Estimation of Heavy-Tailed Distributions. CoRR Gautam Kamath, Vikrant Singhal, Jonathan R. Ullman
2020	A*	`conf`	Private Query Release Assisted by Public Data. ICML Raef Bassily, Albert Cheu, Shay Moran, Aleksandar Nikolov, Jonathan R. Ullman, Zhiwei Steven Wu
2020	J	`jnl`	Private Query Release Assisted by Public Data. CoRR Raef Bassily, Albert Cheu, Shay Moran, Aleksandar Nikolov, Jonathan R. Ullman, Zhiwei Steven Wu
2020	J	`jnl`	The Limits of Pan Privacy and Shuffle Privacy for Learning and Estimation. CoRR Albert Cheu, Jonathan R. Ullman
2020	A*	`conf`	The power of factorization mechanisms in local and central differential privacy. STOC Alexander Edmonds, Aleksandar Nikolov, Jonathan R. Ullman
2019	A*	`conf`	Differentially Private Algorithms for Learning Mixtures of Separated Gaussians. NeurIPS Gautam Kamath, Or Sheffet, Vikrant Singhal, Jonathan R. Ullman
2019	J	`jnl`	Differentially Private Algorithms for Learning Mixtures of Separated Gaussians. CoRR Gautam Kamath, Or Sheffet, Vikrant Singhal, Jonathan R. Ullman
2019	A*	`conf`	Differentially Private Fair Learning. ICML Matthew Jagielski, Michael J. Kearns, Jieming Mao, Alina Oprea, Aaron Roth, Saeed Sharifi-Malvajerdi, Jonathan R. Ullman
2019	—	`conf`	Distributed Differential Privacy via Shuffling. EUROCRYPT (1) Albert Cheu, Adam D. Smith, Jonathan R. Ullman, David Zeber, Maxim Zhilyaev
2019	J	`jnl`	Distributed Differential Privacy via Shuffling. IACR Cryptol. ePrint Arch. Albert Cheu, Adam D. Smith, Jonathan R. Ullman, David Zeber, Maxim Zhilyaev
2019	J	`jnl`	Editorial for Volume 9 Issue 2. J. Priv. Confidentiality Jonathan R. Ullman, Lars Vilhuber
2019	J	`jnl`	Efficient Private Algorithms for Learning Halfspaces. CoRR Huy L. Nguyen, Jonathan R. Ullman, Lydia Zakynthinou
2019	A*	`conf`	Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy. NeurIPS Jonathan R. Ullman, Adam Sealfon
2019	J	`jnl`	Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy. CoRR Adam Sealfon, Jonathan R. Ullman
2019	J	`jnl`	Make Up Your Mind: The Price of Online Queries in Differential Privacy. J. Priv. Confidentiality Mark Bun, Thomas Steinke, Jonathan R. Ullman
2019	J	`jnl`	Manipulation Attacks in Local Differential Privacy. CoRR Albert Cheu, Adam D. Smith, Jonathan R. Ullman
2019	J	`jnl`	Private Identity Testing for High-Dimensional Distributions. CoRR Clément L. Canonne, Gautam Kamath, Audra McMillan, Jonathan R. Ullman, Lydia Zakynthinou
2019	A*	`conf`	Privately Learning High-Dimensional Distributions. COLT Gautam Kamath, Jerry Li, Vikrant Singhal, Jonathan R. Ullman
2019	J	`jnl`	Program for TPDP 2017. J. Priv. Confidentiality Jonathan R. Ullman, Lars Vilhuber
2019	A*	`conf`	Securely Sampling Biased Coins with Applications to Differential Privacy. CCS Jeffrey Champion, Abhi Shelat, Jonathan R. Ullman
2019	J	`jnl`	Securely Sampling Biased Coins with Applications to Differential Privacy. IACR Cryptol. ePrint Arch. Jeffrey Champion, Abhi Shelat, Jonathan R. Ullman
2019	J	`jnl`	The Power of Factorization Mechanisms in Local and Central Differential Privacy. CoRR Alexander Edmonds, Aleksandar Nikolov, Jonathan R. Ullman
2019	A*	`conf`	The structure of optimal private tests for simple hypotheses. STOC Clément L. Canonne, Gautam Kamath, Audra McMillan, Adam D. Smith, Jonathan R. Ullman
2018	J	`jnl`	Computing marginals using MapReduce. J. Comput. Syst. Sci. Foto N. Afrati, Shantanu Sharma, Jonathan R. Ullman, Jeffrey D. Ullman
2018	J	`jnl`	Differentially Private Fair Learning. CoRR Matthew Jagielski, Michael J. Kearns, Jieming Mao, Alina Oprea, Aaron Roth, Saeed Sharifi-Malvajerdi, Jonathan R. Ullman
2018	J	`jnl`	Distributed Differential Privacy via Mixnets. CoRR Albert Cheu, Adam D. Smith, Jonathan R. Ullman, David Zeber, Maxim Zhilyaev
2018	J	`jnl`	Fingerprinting Codes and the Price of Approximate Differential Privacy. SIAM J. Comput. Mark Bun, Jonathan R. Ullman, Salil P. Vadhan
2018	—	`conf`	Hardness of Non-interactive Differential Privacy from One-Way Functions. CRYPTO (1) Lucas Kowalczyk, Tal Malkin, Jonathan R. Ullman, Daniel Wichs
2018	A*	`conf`	Local Differential Privacy for Evolving Data. NeurIPS Matthew Joseph, Aaron Roth, Jonathan R. Ullman, Bo Waggoner
2018	J	`jnl`	Local Differential Privacy for Evolving Data. CoRR Matthew Joseph, Aaron Roth, Jonathan R. Ullman, Bo Waggoner
2018	J	`jnl`	Privately Learning High-Dimensional Distributions. CoRR Gautam Kamath, Jerry Li, Vikrant Singhal, Jonathan R. Ullman
2018	B	`conf`	Skyline Identification in Multi-Arm Bandits. ISIT Albert Cheu, Ravi Sundaram, Jonathan R. Ullman
2018	J	`jnl`	The Fienberg Problem: How to Allow Human Interactive Data Analysis in the Age of Differential Privacy. J. Priv. Confidentiality Cynthia Dwork, Jonathan R. Ullman
2018	A*	`conf`	The Limits of Post-Selection Generalization. NeurIPS Jonathan R. Ullman, Adam D. Smith, Kobbi Nissim, Uri Stemmer, Thomas Steinke
2018	J	`jnl`	The Limits of Post-Selection Generalization. CoRR Kobbi Nissim, Adam D. Smith, Thomas Steinke, Uri Stemmer, Jonathan R. Ullman
2018	J	`jnl`	The Structure of Optimal Private Tests for Simple Hypotheses. CoRR Clément L. Canonne, Gautam Kamath, Audra McMillan, Adam D. Smith, Jonathan R. Ullman
2017	J	`jnl`	An Antifolk Theorem for Large Repeated Games. ACM Trans. Economics and Comput. Mallesh M. Pai, Aaron Roth, Jonathan R. Ullman
2017	—	`conf`	Fractional Set Cover in the Streaming Model. APPROX-RANDOM Piotr Indyk, Sepideh Mahabadi, Ronitt Rubinfeld, Jonathan R. Ullman, Ali Vakilian, Anak Yodpinyanee
2017	J	`jnl`	Hardness of Non-Interactive Differential Privacy from One-Way Functions. IACR Cryptol. ePrint Arch. Lucas Kowalczyk, Tal Malkin, Jonathan R. Ullman, Daniel Wichs
2017	A*	`conf`	Make Up Your Mind: The Price of Online Queries in Differential Privacy. SODA Mark Bun, Thomas Steinke, Jonathan R. Ullman
2017	A*	`conf`	Multidimensional Dynamic Pricing for Welfare Maximization. EC Aaron Roth, Aleksandrs Slivkins, Jonathan R. Ullman, Zhiwei Steven Wu
2017	J	`jnl`	Skyline Identification in Multi-Armed Bandits. CoRR Albert Cheu, Ravi Sundaram, Jonathan R. Ullman
2017	J	`jnl`	Subgaussian Tail Bounds via Stability Arguments. CoRR Thomas Steinke, Jonathan R. Ullman
2017	J	`jnl`	Technical Perspective: Building a safety net for data reuse. Commun. ACM Jonathan R. Ullman
2017	A*	`conf`	The Price of Selection in Differential Privacy. COLT Mitali Bafna, Jonathan R. Ullman
2017	J	`jnl`	The Price of Selection in Differential Privacy. CoRR Mitali Bafna, Jonathan R. Ullman
2017	A*	`conf`	Tight Lower Bounds for Differentially Private Selection. FOCS Thomas Steinke, Jonathan R. Ullman
2017	J	`jnl`	Tight Lower Bounds for Differentially Private Selection. CoRR Thomas Steinke, Jonathan R. Ullman
2016	A*	`conf`	Algorithmic stability for adaptive data analysis. STOC Raef Bassily, Kobbi Nissim, Adam D. Smith, Thomas Steinke, Uri Stemmer, Jonathan R. Ullman
2016	J	`jnl`	Answering n SIAM J. Comput. Jonathan R. Ullman
2016	J	`jnl`	Between Pure and Approximate Differential Privacy. J. Priv. Confidentiality Thomas Steinke, Jonathan R. Ullman
2016	C	`conf`	Computing Marginals Using MapReduce: Keynote talk paper. IDEAS Foto N. Afrati, Shantanu Sharma, Jeffrey D. Ullman, Jonathan R. Ullman
2016	Misc	`conf`	Interactive fingerprinting codes and the hardness of preventing false discovery. ITA Thomas Steinke, Jonathan R. Ullman
2016	J	`jnl`	Make Up Your Mind: The Price of Online Queries in Differential Privacy. CoRR Mark Bun, Thomas Steinke, Jonathan R. Ullman
2016	J	`jnl`	Multidimensional Dynamic Pricing for Welfare Maximization. CoRR Aaron Roth, Aleksandrs Slivkins, Jonathan R. Ullman, Zhiwei Steven Wu
2016	J	`jnl`	PSI (Ψ): a Private data Sharing Interface. CoRR Marco Gaboardi, James Honaker, Gary King, Kobbi Nissim, Jonathan R. Ullman, Salil P. Vadhan
2016	—	`conf`	Privacy Odometers and Filters: Pay-as-you-Go Composition. NIPS Ryan M. Rogers, Salil P. Vadhan, Aaron Roth, Jonathan R. Ullman
2016	J	`jnl`	Privacy Odometers and Filters: Pay-as-you-Go Composition. CoRR Ryan M. Rogers, Aaron Roth, Jonathan R. Ullman, Salil P. Vadhan
2016	—	`ch.`	Query Release via Online Learning. Encyclopedia of Algorithms Jonathan R. Ullman
2016	J	`jnl`	Some Pairs Problems. CoRR Jeffrey D. Ullman, Jonathan R. Ullman
2016	—	`conf`	Some pairs problems. BeyondMR@SIGMOD Jeffrey D. Ullman, Jonathan R. Ullman
2016	A*	`conf`	Space Lower Bounds for Itemset Frequency Sketches. PODS Edo Liberty, Michael Mitzenmacher, Justin Thaler, Jonathan R. Ullman
2016	—	`conf`	Strong Hardness of Privacy from Weak Traitor Tracing. TCC (B1) Lucas Kowalczyk, Tal Malkin, Jonathan R. Ullman, Mark Zhandry
2016	J	`jnl`	Strong Hardness of Privacy from Weak Traitor Tracing. CoRR Lucas Kowalczyk, Tal Malkin, Jonathan R. Ullman, Mark Zhandry
2016	J	`jnl`	Strong Hardness of Privacy from Weak Traitor Tracing. IACR Cryptol. ePrint Arch. Lucas Kowalczyk, Tal Malkin, Jonathan R. Ullman, Mark Zhandry
2016	A*	`conf`	Watch and learn: optimizing from revealed preferences feedback. STOC Aaron Roth, Jonathan R. Ullman, Zhiwei Steven Wu
2016	J	`jnl`	When Can Limited Randomness Be Used in Repeated Games? Theory Comput. Syst. Pavel Hubácek, Moni Naor, Jonathan R. Ullman
2015	J	`jnl`	Algorithmic Stability for Adaptive Data Analysis. CoRR Raef Bassily, Kobbi Nissim, Adam D. Smith, Thomas Steinke, Uri Stemmer, Jonathan R. Ullman
2015	J	`jnl`	Between Pure and Approximate Differential Privacy. CoRR Thomas Steinke, Jonathan R. Ullman
2015	J	`jnl`	Computing Marginals Using MapReduce. CoRR Foto N. Afrati, Shantanu Sharma, Jeffrey D. Ullman, Jonathan R. Ullman
2015	A*	`conf`	Inducing Approximately Optimal Flow Using Truthful Mediators. EC Ryan M. Rogers, Aaron Roth, Jonathan R. Ullman, Zhiwei Steven Wu
2015	J	`jnl`	Inducing Approximately Optimal Flow Using Truthful Mediators. CoRR Ryan M. Rogers, Aaron Roth, Jonathan R. Ullman, Zhiwei Steven Wu
2015	A*	`conf`	Interactive Fingerprinting Codes and the Hardness of Preventing False Discovery. COLT Thomas Steinke, Jonathan R. Ullman
2015	A*	`conf`	Private Multiplicative Weights Beyond Linear Queries. PODS Jonathan R. Ullman
2015	J	`jnl`	Robust Mediators in Large Games. CoRR Michael J. Kearns, Mallesh M. Pai, Ryan M. Rogers, Aaron Roth, Jonathan R. Ullman
2015	A*	`conf`	Robust Traceability from Trace Amounts. FOCS Cynthia Dwork, Adam D. Smith, Thomas Steinke, Jonathan R. Ullman, Salil P. Vadhan
2015	J	`jnl`	Watch and Learn: Optimizing from Revealed Preferences Feedback. CoRR Aaron Roth, Jonathan R. Ullman, Zhiwei Steven Wu
2015	J	`jnl`	Watch and learn: optimizing from revealed preferences feedback. SIGecom Exch. Aaron Roth, Jonathan R. Ullman, Zhiwei Steven Wu
2015	B	`conf`	When Can Limited Randomness Be Used in Repeated Games? SAGT Pavel Hubácek, Moni Naor, Jonathan R. Ullman
2015	J	`jnl`	When Can Limited Randomness Be Used in Repeated Games? CoRR Pavel Hubácek, Moni Naor, Jonathan R. Ullman
2014	J	`jnl`	An Anti-Folk Theorem for Large Repeated Games with Imperfect Monitoring. CoRR Mallesh M. Pai, Aaron Roth, Jonathan R. Ullman
2014	A	`conf`	Faster private release of marginals on small databases. ITCS Karthekeyan Chandrasekaran, Justin Thaler, Jonathan R. Ullman, Andrew Wan
2014	A*	`conf`	Fingerprinting codes and the price of approximate differential privacy. STOC Mark Bun, Jonathan R. Ullman, Salil P. Vadhan
2014	J	`jnl`	Interactive Fingerprinting Codes and the Hardness of Preventing False Discovery. CoRR Thomas Steinke, Jonathan R. Ullman
2014	A	`conf`	Mechanism design in large games: incentives and privacy. ITCS Michael J. Kearns, Mallesh M. Pai, Aaron Roth, Jonathan R. Ullman
2014	A*	`conf`	Preventing False Discovery in Interactive Data Analysis Is Hard. FOCS Moritz Hardt, Jonathan R. Ullman
2014	J	`jnl`	Preventing False Discovery in Interactive Data Analysis is Hard. CoRR Moritz Hardt, Jonathan R. Ullman
2014	J	`jnl`	Private Multiplicative Weights Beyond Linear Queries. CoRR Jonathan R. Ullman
2014	—	`conf`	Privately Solving Linear Programs. ICALP (1) Justin Hsu, Aaron Roth, Tim Roughgarden, Jonathan R. Ullman
2014	J	`jnl`	Privately Solving Linear Programs. CoRR Justin Hsu, Aaron Roth, Tim Roughgarden, Jonathan R. Ullman
2013	A*	`conf`	Answering n STOC Jonathan R. Ullman
2013	A*	`conf`	Differential privacy for the analyst via private equilibrium computation. STOC Justin Hsu, Aaron Roth, Jonathan R. Ullman
2013	J	`jnl`	Faster Private Release of Marginals on Small Databases CoRR Karthekeyan Chandrasekaran, Justin Thaler, Jonathan R. Ullman, Andrew Wan
2013	J	`jnl`	Fingerprinting Codes and the Price of Approximate Differential Privacy. CoRR Mark Bun, Jonathan R. Ullman, Salil P. Vadhan
2013	J	`jnl`	Privately Releasing Conjunctions and the Statistical Query Barrier. SIAM J. Comput. Anupam Gupta, Moritz Hardt, Aaron Roth, Jonathan R. Ullman
2012	J	`jnl`	Answering n^{2+o(1)} Counting Queries with Differential Privacy is Hard CoRR Jonathan R. Ullman
2012	J	`jnl`	Differential Privacy for the Analyst via Private Equilibrium Computation CoRR Justin Hsu, Aaron Roth, Jonathan R. Ullman
2012	J	`jnl`	Faster Algorithms for Privately Releasing Marginals CoRR Justin Thaler, Jonathan R. Ullman, Salil P. Vadhan
2012	—	`conf`	Faster Algorithms for Privately Releasing Marginals. ICALP (1) Justin Thaler, Jonathan R. Ullman, Salil P. Vadhan
2012	B	`conf`	Iterative Constructions and Private Data Release. TCC Anupam Gupta, Aaron Roth, Jonathan R. Ullman
2011	J	`jnl`	Iterative Constructions and Private Data Release CoRR Anupam Gupta, Aaron Roth, Jonathan R. Ullman
2011	J	`jnl`	On the Zero-Error Capacity Threshold for Deletion Channels CoRR Ian A. Kash, Michael Mitzenmacher, Justin Thaler, Jonathan R. Ullman
2011	Misc	`conf`	On the zero-error capacity threshold for deletion channels. ITA Ian A. Kash, Michael Mitzenmacher, Justin Thaler, Jonathan R. Ullman
2011	B	`conf`	PCPs and the Hardness of Generating Private Synthetic Data. TCC Jonathan R. Ullman, Salil P. Vadhan
2011	A*	`conf`	Privately releasing conjunctions and the statistical query barrier. STOC Anupam Gupta, Moritz Hardt, Aaron Roth, Jonathan R. Ullman
2010	—	`conf`	Course Allocation by Proxy Auction. WINE Scott Duke Kominers, Mike Ruberry, Jonathan R. Ullman
2010	J	`jnl`	PCPs and the Hardness of Generating Synthetic Data. Electron. Colloquium Comput. Complex. Jonathan R. Ullman, Salil P. Vadhan
2010	J	`jnl`	Privately Releasing Conjunctions and the Statistical Query Barrier CoRR Anupam Gupta, Moritz Hardt, Aaron Roth, Jonathan R. Ullman
2010	A*	`conf`	The price of privately releasing contingency tables and the spectra of random matrices with correlated rows. STOC Shiva Prasad Kasiviswanathan, Mark Rudelson, Adam D. Smith, Jonathan R. Ullman