Research Papers
I am committed to making all of my papers freely available as quickly as possible by hosting them on arXiv, and these preprints should be considered the authoritative version of the paper. When possible I will also link to any associated code, data, talks, or expository writing available. These resources are indicated with paper talk code misc tags.
I prefer not to order authors by contribution, but sometimes the norms of the community and the needs of students demand it. Author ordering is alphabetical except where otherwise noted.
Manuscripts
Efficient and Optimal Learning of Discrete Distributions with Person-Level Privacy
Preprint
The Sample Complexity of Membership Inference and Privacy Auditing arXiv
Preprint
Instance-Optimal Differentially Private Estimation arXiv
Preprint
Conference and other Primary Publications
Like most computer scientists, my work is primarily published in competitive conferences, which are typically as selective as top journals. This list includes all primary publications of my work in regardless of venue.
2026
Online Matrix Factorization, Online Private Query Release, and Online Discrepancy Minimization
STOC ’26 — ACM Symposium on Theory of Computing
Black-Box Privacy Attacks on Shared Representations in Multitask Learning arXiv
ICLR ’26 — International Conference on Learning Representations
Lower Bounds for Public-Private Learning Under Distribution Shift arXiv
AISTATS ’26 — International Conference on Artificial Intelligence and Statistics
2025
A Bias-Variance-Privacy Trilemma for Statistical Estimation arXiv
Journal of the American Statistical Association ’25
Privacy in Metalearning and Multitask Learning: Modeling and Separations arXiv
AISTATS ’25 — International Conference on Artificial Intelligence and Statistics
Private Mean Estimation with Person-Level Differential Privacy arXiv
SODA ’25 — ACM-SIAM Symposium on Discrete Algorithms
2024
Private Geometric Median arXiv
NeurIPS ’24 — Conference on Neural and Information Processing Systems
Metalearning with Very Few Samples Per Task arXiv
COLT ’24 — Conference on Learning Theory
Smooth Lower Bounds for Differentially Private Algorithms via Padding-and-Permuting Fingerprinting Codes arXiv
COLT ’24 — Conference on Learning Theory
How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization arXiv
ICML ’24 — International Conference on Machine Learning
Program Analysis for Adaptive Data Analysis
PLDI ’24 — Conference on Programming Languages Design and Implementation
TMI! Finetuned Models Leak Private Information from their Pretraining Data arXiv
PETS ’24 — Privacy Enhancing Technologies Symposium
Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning arXiv Video GitHub
ICLR ’24 — International Conference on Learning Representations
Differentially Private Medians and Interior Points for Non-Pathological Data arXiv
ITCS ’24 — Innovations in Theoretical Computer Science
2023
Fair and Useful Cohort Selection arXiv
TMLR ’23 — Transactions on Machine Learning Research
Visual Utility Evaluation of Differentially Private Scatterplots IEEE Xplore
IEEE TVCG ’23 — IEEE Transactions on Visualization and Computer Graphics
Multitask Learning via Shared Features: Algorithms and Hardness arXiv
COLT ’23 — Conference on Learning Theory
From Robustness to Privacy and Back arXiv
ICML ’23 — International Conference on Machine Learning
How to Combine Membership-Inference Attacks on Multiple Updated Models arXiv
PETS ’23 — Privacy Enhancing Technologies Symposium
SNAP: Efficient Extraction of Private Properties with Poisoning arXiv 15m Video GitHub
IEEE S&P ’23 — IEEE Symposium on Security and Privacy
2022
A Private and Computationally Efficient Estimator for Unbounded Gaussians arXiv
COLT ’22 — Conference on Learning Theory
2021
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation arXiv
NeurIPS ’21 — Conference on Neural and Information Processing Systems
Selected as a Spotlight Presentation
Leveraging Public Data for Practical Private Query Release arXiv 60m Video
ICML ’21 — International Conference on Machine Learning
The Limits of Pan Privacy and Shuffle Privacy for Learning and Estimation arXiv 60m Video
STOC ’21 — ACM Symposium on Theory of Computing
Manipulation Attacks in Local Differential Privacy arXiv 1m Video
IEEE S&P ’21 — IEEE Symposium on Security and Privacy
2020
Auditing Differentially Private Machine Learning: How Private is Private SGD? arXiv 15m Video GitHub
NeurIPS ’20 — Conference on Neural and Information Processing Systems
CoinPress: Practical Private Mean and Covariance Estimation arXiv GitHub
NeurIPS ’20 — Conference on Neural and Information Processing Systems
Private Identity Testing for High-Dimensional Distributions arXiv
NeurIPS ’20 — Conference on Neural and Information Processing Systems
Selected as a Spotlight Presentation
Private Query Release Assisted by Public Data arXiv 15m Video
ICML ’20 — International Conference on Machine Learning
Private Mean Estimation of Heavy-Tailed Distributions arXiv
COLT ’20 — Conference on Learning Theory
The Power of Factorization Mechanisms in Local and Central Differential Privacy arXiv
STOC ’20 — ACM Symposium on Theory of Computing
Efficient Private Algorithms for Learning Large-Margin Halfspaces arXiv
ALT ’20 — Conference on Algorithmic Learning Theory
2019
Differentially Private Algorithms for Learning Mixtures of Gaussians arXiv
NeurIPS ’19 — Conference on Neural and Information Processing Systems
Efficiently Estimating Erdős-Rényi Graphs with Differential Privacy arXiv Poster
NeurIPS ’19 — Conference on Neural and Information Processing Systems
Securely Sampling Biased Coins with Applications to Differential Privacy ePrint
CCS ’19 — ACM Conference on Computer Security
Differentially Private Fair Learning arXiv
ICML ’19 — International Conference on Machine Learning
Privately Learning High-Dimensional Distributions arXiv Talk Video
COLT ’19 — Conference on Learning Theory
The Structure of Optimal Private Tests for Simple Hypotheses arXiv Talk Video
STOC ’19 — ACM Symposium on Theory of Computing
Distributed Differential Privacy via Shuffling arXiv
EUROCRYPT ’19 — IACR International Conference on Theory and Application of Cryptographic Techniques
2018
The Fienberg Problem: How to Allow Human Interactive Data Analysis in the Age of Differential Privacy
Journal of Privacy and Confidentiality '18
Computing Marginals Using MapReduce arXiv
Journal of Computer and Systems Science ’18
Local Differential Privacy for Evolving Data arXiv
NeurIPS ’18 — Conference on Neural and Information Processing Systems
Selected as a Spotlight Presentation
The Limits of Post-Selection Generalization arXiv
NeurIPS ’18 — Conference on Neural and Information Processing Systems
Hardness of Non-Interactive Differential Privacy from One-Way Functions ePrint
CRYPTO ’18 — IACR International Cryptology Conference
Skyline Identification in Multi-Armed Bandits arXiv
ISIT ’18 — IEEE International Symposium on Information Theory
2017
An Antifolk Theorem for Large Repeated Games arXiv
ACM Transactions on Economics and Computation ’17
Between Pure and Approximate Differential Privacy arXiv
Journal of Privacy and Confidentiality ’17
Tight Bounds for Differentially Private Selection arXiv
FOCS ’17 — IEEE Symposium on Foundations of Computer Science
Fractional Set Cover in the Streaming Model arXiv
APPROX ’17 — International Workshop on Approximation Algorithms for Combinatorial Optimization Problems
The Price of Selection in Differential Privacy arXiv
COLT ’17 — Conference on Computational Learning Theory
Multidimensional Dynamic Pricing for Welfare Maximization arXiv
EC ’17 — ACM Conference on Economics and Computation
Invited to a special issue of Transactions on Economics and Computation for EC ’17
Make Up Your Mind: The Price of Online Queries in Differential Privacy arXiv
SODA ’17 — ACM-SIAM Symposium on Discrete Algorithms
2016
Privacy Odometers and Filters: Pay-as-you-go Composition arXiv
NeurIPS ’16 — Conference on Neural and Information Processing Systems
Strong Hardness of Privacy from Weak Traitor Tracing arXiv
TCC ’16B — IACR Theory of Cryptography Conference
Space Lower Bounds for Itemset Frequency Sketches arXiv
PODS ’16 — ACM Symposium on Principles of Database Systems
Algorithmic Stability for Adaptive Data Analysis arXiv
STOC ’16 — ACM Symposium on Theory of Computing
Invited to a special issue of SIAM Journal on Computing for STOC ’16
Watch and Learn: Optimizing from Revealed Preferences Feedback arXiv SIGEcom Exchanges
STOC ’16 — ACM Symposium on Theory of Computing
2015
When Can Limited Randomness Be Used in Repeated Games? arXiv
SAGT ’15 — International Symposium on Algorithmic Game Theory
Invited to a special issue of Theory of Computing for SAGT ’15
Robust Traceability from Trace Amounts PDF
FOCS ’15 — IEEE Symposium on Foundations of Computer Science
Interactive Fingerprinting Codes and the Hardness of Preventing False Discovery arXiv
COLT ’15 — Conference on Computational Learning Theory
Inducing Approximately Optimal Flow Using Truthful Mediators arXiv
EC ’15 — ACM Conference on Economics and Computation
Private Multiplicative Weights Beyond Linear Queries arXiv
PODS ’15 — ACM Symposium on Principles of Database Systems
2014
Preventing False Discovery in Interactive Data Analysis is Hard arXiv
FOCS ’14 — IEEE Symposium on Foundations of Computer Science
Privately Solving Linear Programs arXiv
ICALP ’14 — International Colloquium on Automata, Languages, and Programming Track A
Fingerprinting Codes and the Price of Approximate Differential Privacy arXiv
STOC ’14 — ACM Symposium on Theory of Computing
Invited to a special issue of SIAM Journal of Computing for STOC ’14
Faster Private Release of Marginals on Small Databases arXiv
ITCS ’14 — Innovations in Theoretical Computer Science
Robust Mediators in Large Games arXiv
ITCS ’14 — Innovations in Theoretical Computer Science
2013
Differential Privacy for the Analyst via Private Equilibrium Computation arXiv
STOC ’13 — ACM Symposium on Thoery of Computing
Answering n2+o(1) Counting Queries with Differential Privacy is Hard arXiv
STOC ’13 — ACM Symposium on Thoery of Computing
Invited to a special issue of SIAM Journal of Computing for STOC ’13
2012
Faster Algorithms for Privately Releasing Marginals arXiv
ICALP ’12 — International Colloquium on Automata, Languages, and Programming Track A
Iterative Constructions and Private Data Release arXiv
TCC ’12 — IACR Theory of Cryptography Conference
Privately Releasing Conjunctions and the Statistical Query Barrier arXiv
STOC ’12 — ACM Symposium on Theory of Computing
2011
PCPs and the Hardness of Generating Private Synthetic Data ECCC
TCC ’11 — IACR Theory of Cryptography Conference
Invited to the Journal of Cryptology
2010
Course Allocation by Proxy Auction
WINE ’10 — Workshop on Internet and Network Economics
The Price of Privately Releasing Contingency Tables and the Spectra of Random Matrices with Correlated Rows
STOC ’10 — ACM Symposium on Theory of Computing
Secondary Publications
Some of my work appears in journals as a secondary form of publication, after initially appearing in a computer science conference. This list includes all such publications.
Manipulation Attacks in Local Differential Privacy arXiv 1m Video
Journal of Privacy and Confidentiality ’21
Efficiently Estimating Erdős–Rényi Graphs with Differential Privacy arXiv Poster
Journal of Privacy and Confidentiality ’21
PCPs and the Hardness of Generating Private Synthetic Data ECCC
JoC ’20 — Journal of Cryptology
Invited submission from TCC ’11
Multidimensional Dynamic Pricing for Welfare Maximization
TEAC ’20 — ACM Transactions on Economics and Computation
Special issue for invited papers from EC ’17
Fingerprinting Codes and the Price of Approximate Differential Privacy arXiv
SICOMP ’18 — SIAM Journal on Computing
Special issue for invited papers from STOC ’14
When Can Limited Randomness Be Used in Repeated Games? arXiv
ToCS ’16 — Theory of Computing Systems
Special issue for invited papers from SAGT ’15
Answering n²+o(1) Counting Queries with Differential Privacy is Hard arXiv
SICOMP ’16 — SIAM Journal on Computing
Special issue for invited papers from STOC ’13
Privately Releasing Conjunctions and the Statistical Query Barrier arXiv
SICOMP ’13 — SIAM Journal on Computing
Surveys and Other Writing
DifferentialPrivacy.org Website
Blog
Subgaussian Concentration via Stability Arguments arXiv
Technical Perspective: Building a Safety Net for Data Reuse CACM
Communications of the ACM’17
PSI (Ψ): A Private data Sharing Interface arXiv
Exposed! A Survey of Attacks on Private Data ARSA
Annual Review of Statistics and its Applications '17