AS
Adam Smith
cs.CRcs.LGcs.DSstat.MLmath.STstat.THcs.ITmath.ITquant-phstat.ME
On Valency
published · living versionsW_djds62n2·v1 · currentpublished
A Simple Presentation of Robust Membership Inference Attacks
with Renaud Gaucher, Ephraim Linder, Jonathan Ullman, Lydia Zakynthinou
1 version
W_k3kqhcbd·v1published
Preprints & journals
67 papers in the corpus · 2002–2026Robust Statistical Estimators with Bounded Empirical Sensitivity2605.21860v1 · Valentio Iverson, Gautam Kamath, Argyris Mouzakis et al.2026 · 0 citationsarXiv
Differentially Private Modeling of Disease Transmission within Human Contact Networks2604.07493v1 · Shlomi Hod, Debanuj Nayak, Jason R. Gantenberg et al.2026 · 0 citationsarXiv
Local Node Differential Privacy2602.15802v3 · Sofya Raskhodnikova, Adam Smith, Connor Wagaman et al.2026 · 0 citationsarXiv
High-Dimensional Privacy-Utility Dynamics of Noisy Stochastic Gradient Descent on Least Squares2510.16687v1 · Shurong Lin, Eric D. Kolaczyk, Adam Smith et al.2025 · 0 citationsarXiv
The Sample Complexity of Membership Inference and Privacy Auditing2508.19458v2 · Mahdi Haghifam, Adam Smith, Jonathan Ullman2025 · 0 citationsarXiv
A Unified Framework for Adversary-Aware Differential Privacy Bounds2507.08158v2 · Marika Swanberg, Meenatchi Sundaram Muthu Selva Annamalai, Jamie Hayes et al.2025 · 0 citationsarXiv
Black-Box Privacy Attacks on Shared Representations in Multitask Learning2506.16460v1 · John Abascal, Nicol'as Berrios, Alina Oprea et al.2025 · 0 citationsarXiv
Generate-then-Verify: Reconstructing Data from Limited Published Statistics2504.21199v2 · Terrance Liu, Eileen Xiao, Adam Smith et al.2025 · 0 citationsarXiv
Privately Evaluating Untrusted Black-Box Functions2503.19268v2 · Ephraim Linder, Sofya Raskhodnikova, Adam Smith et al.2025 · 1 citationarXiv
It's My Data Too: Private ML for Datasets with Multi-User Training Examples2503.03622v1 · Arun Ganesh, Ryan McKenna, Brendan McMahan et al.2025 · 0 citationsarXiv
Privacy in Metalearning and Multitask Learning: Modeling and Separations2412.12374v1 · Maryam Aliakbarpour, Konstantina Bairaktari, Adam Smith et al.2024 · 0 citationsarXiv
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD2410.06186v4 · Thomas Steinke, Milad Nasr, Arun Ganesh et al.2024 · 1 citationarXiv
Auditing Privacy Mechanisms via Label Inference Attacks2406.02797v1 · R'obert Istv'an Busa-Fekete, Travis Dick, Claudio Gentile et al.2024 · 2 citationsarXiv
Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares2404.15409v1 · Gavin Brown, Jonathan Hayase, Samuel Hopkins et al.2024 · 1 citationarXiv
Time-Aware Projections: Truly Node-Private Graph Statistics under Continual Observation2403.04630v2 · Palak Jain, Adam Smith, Connor Wagaman2024 · 5 citationsarXiv
Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation2402.13531v1 · Gavin Brown, Krishnamurthy Dvijotham, Georgina Evans et al.2024 · 0 citationsarXiv
Metalearning with Very Few Samples Per Task2312.13978v2 · Maryam Aliakbarpour, Konstantina Bairaktari, Gavin Brown et al.2023 · 0 citationsarXiv
Counting Distinct Elements in the Turnstile Model with Differential Privacy under Continual Observation2306.06723v3 · Palak Jain, Iden Kalemaj, Sofya Raskhodnikova et al.2023 · 1 citationarXiv
Triangle Counting with Local Edge Differential Privacy2305.02263v3 · Talya Eden, Quanquan C. Liu, Sofya Raskhodnikova et al.2023 · 13 citationsarXiv
Node-Differentially Private Estimation of the Number of Connected Components2304.05890v2 · Iden Kalemaj, Sofya Raskhodnikova, Adam Smith et al.2023 · 5 citationsIn Proceedings of the ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems (PODS) 2023
Fast, Sample-Efficient, Affine-Invariant Private Mean and Covariance Estimation for Subgaussian Distributions2301.12250v3 · Gavin Brown, Samuel B. Hopkins, Adam Smith2023 · 4 citationsarXiv
Differentially Private Confidence Intervals for Proportions under Stratified Random Sampling2301.08324v2 · Shurong Lin, Mark Bun, Marco Gaboardi et al.2023 · 9 citationsElectronic Journal of Statistics, Electron. J. Statist. 18(1), 1455-1494, (2024)
Differentially Private Sampling from Distributions2211.08193v1 · Sofya Raskhodnikova, Satchit Sivakumar, Adam Smith et al.2022 · 2 citationsarXiv
Fully Adaptive Composition for Gaussian Differential Privacy2210.17520v1 · Adam Smith, Abhradeep Thakurta2022 · 1 citationarXiv
Instance-Optimal Differentially Private Estimation2210.15819v1 · Audra McMillan, Adam Smith, Jon Ullman2022 · 0 citationsarXiv
Control, Confidentiality, and the Right to be Forgotten2210.07876v2 · Aloni Cohen, Adam Smith, Marika Swanberg et al.2022 · 8 citationsarXiv
Strong Memory Lower Bounds for Learning Natural Models2206.04743v1 · Gavin Brown, Mark Bun, Adam Smith2022 · 4 citationsarXiv
Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams2202.08312v3 · Sergey Denisov, Brendan McMahan, Keith Rush et al.2022 · 15 citationsarXiv
The Price of Differential Privacy under Continual Observation2112.00828v4 · Palak Jain, Sofya Raskhodnikova, Satchit Sivakumar et al.2021 · 14 citationsarXiv
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation2106.13329v3 · Gavin Brown, Marco Gaboardi, Adam Smith et al.2021 · 11 citationsarXiv
Non-parametric Differentially Private Confidence Intervals for the Median2106.10333v2 · Joerg Drechsler, Ira Globus-Harris, Audra McMillan et al.2021 · 9 citationsarXiv
When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning?2012.06421v2 · Gavin Brown, Mark Bun, Vitaly Feldman et al.2020 · 54 citationsSTOC 2021 Pages 123-132
Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy2011.05934v1 · Di Wang, Marco Gaboardi, Adam Smith et al.2020 · 8 citationsarXiv
Differentially Private Simple Linear Regression2007.05157v1 · Daniel Alabi, Audra McMillan, Jayshree Sarathy et al.2020 · 15 citationsarXiv
Manipulation Attacks in Local Differential Privacy1909.09630v1 · Albert Cheu, Adam Smith, Jonathan Ullman2019 · 112 citationsarXiv
Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis1906.09231v2 · Ryan Rogers, Aaron Roth, Adam Smith et al.2019 · 3 citationsarXiv
Noninteractive Locally Private Learning of Linear Models via Polynomial Approximations1812.06825v3 · Di Wang, Adam Smith, Jinhui Xu2018 · 15 citationsarXiv
The Structure of Optimal Private Tests for Simple Hypotheses1811.11148v2 · Cl'ement L. Canonne, Gautam Kamath, Audra McMillan et al.2018 · 53 citationsarXiv
Private Algorithms Can Always Be Extended1810.12518v2 · Christian Borgs, Jennifer Chayes, Adam Smith et al.2018 · 3 citationsarXiv
Revealing Network Structure, Confidentially: Improved Rates for Node-Private Graphon Estimation1810.02183v1 · Christian Borgs, Jennifer Chayes, Adam Smith et al.2018 · 28 citationsarXiv
From Soft Classifiers to Hard Decisions: How fair can we be?1810.02003v2 · Ran Canetti, Aloni Cohen, Nishanth Dikkala et al.2018 · 4 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
Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization1805.10222v3 · Blake Woodworth, Jialei Wang, Adam Smith et al.2018 · 81 citationsarXiv
Information, Privacy and Stability in Adaptive Data Analysis1706.00820v1 · Adam Smith2017 · 7 citationsarXiv
Differentially Private Model Selection with Penalized and Constrained Likelihood1607.04204v1 · Jing Lei, Anne-Sophie Charest, Aleksandra Slavkovic et al.2016 · 24 citationsarXiv
Max-Information, Differential Privacy, and Post-Selection Hypothesis Testing1604.03924v2 · Ryan Rogers, Aaron Roth, Adam Smith et al.2016 · 42 citationsarXiv
When is Nontrivial Estimation Possible for Graphons and Stochastic Block Models?1604.01871v1 · Audra McMillan, Adam Smith2016 · 3 citationsarXiv
Algorithmic Stability for Adaptive Data Analysis1511.02513v1 · Raef Bassily, Kobbi Nissim, Adam Smith et al.2015 · 154 citationsarXiv
Classical Cryptographic Protocols in a Quantum World1507.01625v1 · Sean Hallgren, Adam Smith, Fang Song2015 · 18 citationsInternational Journal of Quantum Information Vol. 13, No. 4 (2015) 1550028 (43 pages)
Career total: at least 265 works. 67 are in this corpus.Showing the 50 most recent.
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