JU
Jonathan Ullman
cs.DScs.LGcs.CRstat.MLcs.GTcs.ITmath.ITcs.CCmath.STstat.TH
On Valency
published · living versionsW_djds62n2·v1 · currentpublished
A Simple Presentation of Robust Membership Inference Attacks
with Renaud Gaucher, Ephraim Linder, Adam Smith, Lydia Zakynthinou
1 version
W_5m2zmfqb·v1published
Preprints & journals
74 papers in the corpus · 2010–2026Truthful Calibration Measures for Sequential Prediction2608.21348v2 · Anagha Gokul, Jason Hartline, Lunjia Hu et al.2026 · 0 citationsarXiv
Program Analysis for Adaptive Data Analysis2608.19575v1 · Jiawen Liu, Weihao Qu, Marco Gaboardi et al.2026 · 2 citationsProc. ACM Program. Lang. 8, PLDI, Article 184 (June 2024)
Online Matrix Factorization, Online Private Query Release, and Online Discrepancy Minimization2605.08358v1 · Aleksandar Nikolov, Haohua Tang, Jonathan Ullman2026 · 0 citationsarXiv
The Sample Complexity of Membership Inference and Privacy Auditing2508.19458v2 · Mahdi Haghifam, Adam Smith, Jonathan Ullman2025 · 0 citationsarXiv
Lower Bounds for Public-Private Learning under Distribution Shift2507.17895v1 · Amrith Setlur, Pratiksha Thaker, Jonathan Ullman2025 · 0 citationsarXiv
Privacy in Metalearning and Multitask Learning: Modeling and Separations2412.12374v1 · Maryam Aliakbarpour, Konstantina Bairaktari, Adam Smith et al.2024 · 0 citationsarXiv
Investigating the Visual Utility of Differentially Private Scatterplots.37405888 · Panavas, Liudas, Crnovrsanin, Tarik, Adams, Jane Lydia et al.2025 · 13 citationsIEEE transactions on visualization and computer graphics. 2024;30(8):5370-5385
Private Geometric Median2406.07407v1 · Mahdi Haghifam, Thomas Steinke, Jonathan Ullman2024 · 0 citationsarXiv
Private Mean Estimation with Person-Level Differential Privacy2405.20405v3 · Sushant Agarwal, Gautam Kamath, Mahbod Majid et al.2024 · 6 citationsarXiv
How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization2402.11173v2 · Andrew Lowy, Jonathan Ullman, Stephen J. Wright2024 · 0 citationsarXiv
Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning2310.03838v2 · Harsh Chaudhari, Giorgio Severi, Alina Oprea et al.2023 · 2 citationsarXiv
Smooth Lower Bounds for Differentially Private Algorithms via Padding-and-Permuting Fingerprinting Codes2307.07604v4 · Naty Peter, Eliad Tsfadia, Jonathan Ullman2023 · 1 citationarXiv
TMI! Finetuned Models Leak Private Information from their Pretraining Data2306.01181v3 · John Abascal, Stanley Wu, Alina Oprea et al.2023 · 10 citationsarXiv
Differentially Private Medians and Interior Points for Non-Pathological Data2305.13440v1 · Maryam Aliakbarpour, Rose Silver, Thomas Steinke et al.2023 · 0 citationsarXiv
From Robustness to Privacy and Back2302.01855v1 · Hilal Asi, Jonathan Ullman, Lydia Zakynthinou2023 · 7 citationsarXiv
A Bias-Accuracy-Privacy Trilemma for Statistical Estimation2301.13334v3 · Gautam Kamath, Argyris Mouzakis, Matthew Regehr et al.2023 · 0 citationsarXiv
Multitask Learning via Shared Features: Algorithms and Hardness2209.03112v1 · Konstantina Bairaktari, Guy Blanc, Li-Yang Tan et al.2022 · 2 citationsarXiv
SNAP: Efficient Extraction of Private Properties with Poisoning2208.12348v2 · Harsh Chaudhari, John Abascal, Alina Oprea et al.2022 · 21 citationsarXiv
How to Combine Membership-Inference Attacks on Multiple Updated Models2205.06369v1 · Matthew Jagielski, Stanley Wu, Alina Oprea et al.2022 · 5 citationsarXiv
A Private and Computationally-Efficient Estimator for Unbounded Gaussians2111.04609v2 · Gautam Kamath, Argyris Mouzakis, Vikrant Singhal et al.2021 · 8 citationsarXiv
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation2106.13329v3 · Gavin Brown, Marco Gaboardi, Adam Smith et al.2021 · 11 citationsarXiv
Leveraging Public Data for Practical Private Query Release2102.08598v2 · Terrance Liu, Giuseppe Vietri, Thomas Steinke et al.2021 · 22 citationsarXiv
Fair and Optimal Cohort Selection for Linear Utilities2102.07684v3 · Konstantina Bairaktari, Huy Le Nguyen, Jonathan Ullman2021 · 1 citationarXiv
The Limits of Pan Privacy and Shuffle Privacy for Learning and Estimation2009.08000v3 · Albert Cheu, Jonathan Ullman2020 · 12 citationsarXiv
Fair and Useful Cohort Selection2009.02207v2 · Konstantina Bairaktari, Paul Langton, Huy L. Nguyen et al.2020 · 2 citationsarXiv
Auditing Differentially Private Machine Learning: How Private is Private SGD?2006.07709v1 · Matthew Jagielski, Jonathan Ullman, Alina Oprea2020 · 92 citationsarXiv
CoinPress: Practical Private Mean and Covariance Estimation2006.06618v3 · Sourav Biswas, Yihe Dong, Gautam Kamath et al.2020 · 27 citationsarXiv
A Primer on Private Statistics2005.00010v1 · Gautam Kamath, Jonathan Ullman2020 · 20 citationsarXiv
Private Query Release Assisted by Public Data2004.10941v1 · Raef Bassily, Albert Cheu, Shay Moran et al.2020 · 12 citationsarXiv
Private Mean Estimation of Heavy-Tailed Distributions2002.09464v3 · Gautam Kamath, Vikrant Singhal, Jonathan Ullman2020 · 34 citationsarXiv
The Power of Factorization Mechanisms in Local and Central Differential Privacy1911.08339v1 · Alexander Edmonds, Aleksandar Nikolov, Jonathan Ullman2019 · 25 citationsarXiv
Manipulation Attacks in Local Differential Privacy1909.09630v1 · Albert Cheu, Adam Smith, Jonathan Ullman2019 · 112 citationsarXiv
Differentially Private Algorithms for Learning Mixtures of Separated Gaussians1909.03951v2 · Gautam Kamath, Or Sheffet, Vikrant Singhal et al.2019 · 17 citationsarXiv
Private Identity Testing for High-Dimensional Distributions1905.11947v3 · Cl'ement L. Canonne, Gautam Kamath, Audra McMillan et al.2019 · 15 citationsarXiv
Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy1905.10477v1 · Adam Sealfon, Jonathan Ullman2019 · 29 citationsarXiv
Efficient Private Algorithms for Learning Large-Margin Halfspaces1902.09009v2 · Huy L. Nguyen, Jonathan Ullman, Lydia Zakynthinou2019 · 4 citationsarXiv
Differentially Private Fair Learning1812.02696v3 · Matthew Jagielski, Michael Kearns, Jieming Mao et al.2018 · 62 citationsarXiv
The Structure of Optimal Private Tests for Simple Hypotheses1811.11148v2 · Cl'ement L. Canonne, Gautam Kamath, Audra McMillan et al.2018 · 53 citationsarXiv
Distributed Differential Privacy via Shuffling1808.01394v3 · Albert Cheu, Adam Smith, Jonathan Ullman et al.2018 · 266 citationsarXiv
The Limits of Post-Selection Generalization1806.06100v2 · Kobbi Nissim, Adam Smith, Thomas Steinke et al.2018 · 10 citationsarXiv
Privately Learning High-Dimensional Distributions1805.00216v3 · Gautam Kamath, Jerry Li, Vikrant Singhal et al.2018 · 39 citationsarXiv
Local Differential Privacy for Evolving Data1802.07128v3 · Matthew Joseph, Aaron Roth, Jonathan Ullman et al.2018 · 67 citationsarXiv
Tight Lower Bounds for Locally Differentially Private Selection1802.02638v2 · Jonathan Ullman2018 · 23 citationsarXiv
Skyline Identification in Multi-Armed Bandits1711.04213v2 · Albert Cheu, Ravi Sundaram, Jonathan Ullman2017 · 0 citationsarXiv
Tight Lower Bounds for Differentially Private Selection1704.03024v1 · Thomas Steinke, Jonathan Ullman2017 · 52 citationsarXiv
The Price of Selection in Differential Privacy1702.02970v1 · Mitali Bafna, Jonathan Ullman2017 · 10 citationsarXiv
Subgaussian Tail Bounds via Stability Arguments1701.03493v2 · Thomas Steinke, Jonathan Ullman2017 · 6 citationsarXiv
PSI ({\Psi}): a Private data Sharing Interface1609.04340v3 · Marco Gaboardi, James Honaker, Gary King et al.2016 · 20 citationsarXiv
Strong Hardness of Privacy from Weak Traitor Tracing1607.06141v1 · Lucas Kowalczyk, Tal Malkin, Jonathan Ullman et al.2016 · 10 citationsarXiv
Multidimensional Dynamic Pricing for Welfare Maximization1607.05397v3 · Aaron Roth, Aleksandrs Slivkins, Jonathan Ullman et al.2016 · 19 citationsarXiv
Career total: 127 works. 74 are in this corpus.Showing the 50 most recent.
Profile built from the corpus for this byline.
Author records are still filling in while the Hub is in alpha. If this is your page, you'll be able to claim it soon. Spot a mistake? Tell us.