Jonathan R. Ullman

CoRR, 2024

Private Mean Estimation with Person-Level Differential Privacy.

[BibT_eX]

[DOI]

CoRR, 2024

Differentially Private Medians and Interior Points for Non-Pathological Data.

[BibT_eX]

[DOI]

Proceedings of the 15th Innovations in Theoretical Computer Science Conference, 2024

How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization.

[BibT_eX]

[DOI]

Andrew Lowy

Stephen J. Wright

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Smooth Lower Bounds for Differentially Private Algorithms via Padding-and-Permuting Fingerprinting Codes.

[BibT_eX]

[DOI]

Naty Peter

Eliad Tsfadia

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Metalearning with Very Few Samples Per Task.

[BibT_eX]

[DOI]

Maryam Aliakbarpour

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

How to Combine Membership-Inference Attacks on Multiple Updated Machine Learning Models.

[BibT_eX]

[DOI]

Proc. Priv. Enhancing Technol., July, 2023

Fair and Useful Cohort Selection.

[BibT_eX]

[DOI]

Niklas Smedemark-Margulies

Paul Langton

Huy L. Nguyen

Trans. Mach. Learn. Res., 2023

Metalearning with Very Few Samples Per Task.

[BibT_eX]

[DOI]

Maryam Aliakbarpour

Gavin Brown

Adam Smith

CoRR, 2023

A Bias-Variance-Privacy Trilemma for Statistical Estimation.

[BibT_eX]

[DOI]

CoRR, 2023

SNAP: Efficient Extraction of Private Properties with Poisoning.

[BibT_eX]

[DOI]

Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023

From Robustness to Privacy and Back.

[BibT_eX]

[DOI]

Hilal Asi

Lydia Zakynthinou

Proceedings of the International Conference on Machine Learning, 2023

Multitask Learning via Shared Features: Algorithms and Hardness.

[BibT_eX]

[DOI]

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Instance-Optimal Differentially Private Estimation.

[BibT_eX]

[DOI]

Audra McMillan

Adam D. Smith

CoRR, 2022

How to Combine Membership-Inference Attacks on Multiple Updated Models.

[BibT_eX]

[DOI]

CoRR, 2022

A Private and Computationally-Efficient Estimator for Unbounded Gaussians.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Algorithmic Stability for Adaptive Data Analysis.

[BibT_eX]

[DOI]

SIAM J. Comput., 2021

Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy.

[BibT_eX]

[DOI]

Adam Sealfon

J. Priv. Confidentiality, 2021

Manipulation Attacks in Local Differential Privacy.

[BibT_eX]

[DOI]

Adam D. Smith

J. Priv. Confidentiality, 2021

The limits of pan privacy and shuffle privacy for learning and estimation.

[BibT_eX]

[DOI]

Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

Covariance-Aware Private Mean Estimation Without Private Covariance Estimation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Leveraging Public Data for Practical Private Query Release.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Multidimensional Dynamic Pricing for Welfare Maximization.

[BibT_eX]

[DOI]

ACM Trans. Economics and Comput., 2020

Local Differential Privacy for Evolving Data.

[BibT_eX]

[DOI]

J. Priv. Confidentiality, 2020

A Primer on Private Statistics.

[BibT_eX]

[DOI]

Gautam Kamath

CoRR, 2020

The power of factorization mechanisms in local and central differential privacy.

[BibT_eX]

[DOI]

Alexander Edmonds

Aleksandar Nikolov

Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020

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

[BibT_eX]

[DOI]

Matthew Jagielski

Alina Oprea

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Private Identity Testing for High-Dimensional Distributions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

CoinPress: Practical Private Mean and Covariance Estimation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Private Query Release Assisted by Public Data.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Private Mean Estimation of Heavy-Tailed Distributions.

[BibT_eX]

[DOI]

Gautam Kamath

Vikrant Singhal

Proceedings of the Conference on Learning Theory, 2020

Efficient Private Algorithms for Learning Large-Margin Halfspaces.

[BibT_eX]

[DOI]

Huy Le Nguyen

Lydia Zakynthinou

Proceedings of the Algorithmic Learning Theory, 2020

2019

Program for TPDP 2017.

[BibT_eX]

[DOI]

Lars Vilhuber

J. Priv. Confidentiality, 2019

Editorial for Volume 9 Issue 2.

[BibT_eX]

[DOI]

Lars Vilhuber

J. Priv. Confidentiality, 2019

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

[BibT_eX]

[DOI]

Mark Bun

J. Priv. Confidentiality, 2019

Distributed Differential Privacy via Shuffling.

[BibT_eX]

[DOI]

IACR Cryptol. ePrint Arch., 2019

Securely Sampling Biased Coins with Applications to Differential Privacy.

[BibT_eX]

[DOI]

Jeffrey Champion

Abhi Shelat

IACR Cryptol. ePrint Arch., 2019

Efficient Private Algorithms for Learning Halfspaces.

[BibT_eX]

[DOI]

Huy L. Nguyen

Lydia Zakynthinou

CoRR, 2019

The structure of optimal private tests for simple hypotheses.

[BibT_eX]

[DOI]

Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019

Differentially Private Algorithms for Learning Mixtures of Separated Gaussians.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Differentially Private Fair Learning.

[BibT_eX]

[DOI]

Saeed Sharifi-Malvajerdi

Proceedings of the 36th International Conference on Machine Learning, 2019

Privately Learning High-Dimensional Distributions.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2019

2018

Fingerprinting Codes and the Price of Approximate Differential Privacy.

[BibT_eX]

[DOI]

Mark Bun

SIAM J. Comput., 2018

The Fienberg Problem: How to Allow Human Interactive Data Analysis in the Age of Differential Privacy.

[BibT_eX]

[DOI]

Cynthia Dwork

J. Priv. Confidentiality, 2018

Computing marginals using MapReduce.

[BibT_eX]

[DOI]

J. Comput. Syst. Sci., 2018

Distributed Differential Privacy via Mixnets.

[BibT_eX]

[DOI]

CoRR, 2018

The Limits of Post-Selection Generalization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Skyline Identification in Multi-Arm Bandits.

[BibT_eX]

[DOI]

Ravi Sundaram

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

2017

An Antifolk Theorem for Large Repeated Games.

[BibT_eX]

[DOI]

Mallesh M. Pai

ACM Trans. Economics and Comput., 2017

Hardness of Non-Interactive Differential Privacy from One-Way Functions.

[BibT_eX]

[DOI]

IACR Cryptol. ePrint Arch., 2017

Skyline Identification in Multi-Armed Bandits.

[BibT_eX]

[DOI]

Ravi Sundaram

CoRR, 2017

Subgaussian Tail Bounds via Stability Arguments.

[BibT_eX]

[DOI]

CoRR, 2017

Technical Perspective: Building a safety net for data reuse.

[BibT_eX]

[DOI]

Commun. ACM, 2017

Tight Lower Bounds for Differentially Private Selection.

[BibT_eX]

[DOI]

Proceedings of the 58th IEEE Annual Symposium on Foundations of Computer Science, 2017

The Price of Selection in Differential Privacy.

[BibT_eX]

[DOI]

Mitali Bafna

Proceedings of the 30th Conference on Learning Theory, 2017

Fractional Set Cover in the Streaming Model.

[BibT_eX]

[DOI]

Proceedings of the Approximation, 2017

2016

Query Release via Online Learning.

[BibT_eX]

[DOI]

Encyclopedia of Algorithms, 2016

Answering n<sup>2+o(1)</sup> Counting Queries with Differential Privacy is Hard.

[BibT_eX]

[DOI]

SIAM J. Comput., 2016

When Can Limited Randomness Be Used in Repeated Games?

[BibT_eX]

[DOI]

Pavel Hubácek

Moni Naor

Theory Comput. Syst., 2016

Between Pure and Approximate Differential Privacy.

[BibT_eX]

[DOI]

J. Priv. Confidentiality, 2016

Strong Hardness of Privacy from Weak Traitor Tracing.

[BibT_eX]

[DOI]

IACR Cryptol. ePrint Arch., 2016

PSI (Ψ): a Private data Sharing Interface.

[BibT_eX]

[DOI]

CoRR, 2016

Some pairs problems.

[BibT_eX]

[DOI]

Jeffrey D. Ullman

Proceedings of the 3rd ACM SIGMOD Workshop on Algorithms and Systems for MapReduce and Beyond, 2016

Space Lower Bounds for Itemset Frequency Sketches.

[BibT_eX]

[DOI]

Proceedings of the 35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, 2016

Privacy Odometers and Filters: Pay-as-you-Go Composition.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Computing Marginals Using MapReduce: Keynote talk paper.

[BibT_eX]

[DOI]

Proceedings of the 20th International Database Engineering & Applications Symposium, 2016

2015

Watch and learn: optimizing from revealed preferences feedback.

[BibT_eX]

[DOI]

Zhiwei Steven Wu

SIGecom Exch., 2015

Robust Mediators in Large Games.

[BibT_eX]

[DOI]

CoRR, 2015

Inducing Approximately Optimal Flow Using Truthful Mediators.

[BibT_eX]

[DOI]

Proceedings of the Sixteenth ACM Conference on Economics and Computation, 2015

Private Multiplicative Weights Beyond Linear Queries.

[BibT_eX]

[DOI]

Proceedings of the 34th ACM Symposium on Principles of Database Systems, 2015

Robust Traceability from Trace Amounts.

[BibT_eX]

[DOI]

Proceedings of the IEEE 56th Annual Symposium on Foundations of Computer Science, 2015

Interactive Fingerprinting Codes and the Hardness of Preventing False Discovery.

[BibT_eX]

[DOI]

Proceedings of The 28th Conference on Learning Theory, 2015

2014

An Anti-Folk Theorem for Large Repeated Games with Imperfect Monitoring.

[BibT_eX]

[DOI]

Mallesh M. Pai

Karthekeyan Chandrasekaran

CoRR, 2014

Mechanism design in large games: incentives and privacy.

[BibT_eX]

[DOI]

Proceedings of the Innovations in Theoretical Computer Science, 2014

Faster private release of marginals on small databases.

[BibT_eX]

[DOI]

Justin Thaler

Andrew Wan

Proceedings of the Innovations in Theoretical Computer Science, 2014

Privately Solving Linear Programs.

[BibT_eX]

[DOI]

Proceedings of the Automata, Languages, and Programming - 41st International Colloquium, 2014

Preventing False Discovery in Interactive Data Analysis Is Hard.

[BibT_eX]

[DOI]

Moritz Hardt

Proceedings of the 55th IEEE Annual Symposium on Foundations of Computer Science, 2014

2013

Privately Releasing Conjunctions and the Statistical Query Barrier.

[BibT_eX]

[DOI]

SIAM J. Comput., 2013

Answering n<sub>{2+o(1)}</sub> counting queries with differential privacy is hard.

[BibT_eX]

[DOI]

Proceedings of the Symposium on Theory of Computing Conference, 2013

Differential privacy for the analyst via private equilibrium computation.

[BibT_eX]

[DOI]

Justin Hsu

Proceedings of the Symposium on Theory of Computing Conference, 2013

2012

Answering n^{2+o(1)} Counting Queries with Differential Privacy is Hard

[BibT_eX]

[DOI]

CoRR, 2012

Iterative Constructions and Private Data Release.

[BibT_eX]

[DOI]

Anupam Gupta

Proceedings of the Theory of Cryptography - 9th Theory of Cryptography Conference, 2012

Faster Algorithms for Privately Releasing Marginals.

[BibT_eX]

[DOI]

Justin Thaler

Proceedings of the Automata, Languages, and Programming - 39th International Colloquium, 2012

2011

PCPs and the Hardness of Generating Private Synthetic Data.

[BibT_eX]

[DOI]

Proceedings of the Theory of Cryptography - 8th Theory of Cryptography Conference, 2011

On the zero-error capacity threshold for deletion channels.

[BibT_eX]

[DOI]

Proceedings of the Information Theory and Applications Workshop, 2011

2010

PCPs and the Hardness of Generating Synthetic Data.

[BibT_eX]

[DOI]

Electron. Colloquium Comput. Complex., 2010

Course Allocation by Proxy Auction.

[BibT_eX]

[DOI]

Scott Duke Kominers

Mike Ruberry

Shiva Prasad Kasiviswanathan

Proceedings of the Internet and Network Economics - 6th International Workshop, 2010

The price of privately releasing contingency tables and the spectra of random matrices with correlated rows.

[BibT_eX]

[DOI]

Mark Rudelson

Adam D. Smith