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Fingerprinting arguments, first introduced by Bun, Ullman, and Vadhan (STOC 2014), are the most widely used method for establishing lower bounds on the sample complexity or error of approximately differentially private (DP) algorithms.
“Privately Learning High-Dimensional Distributions”
Gautam Kamath, Jerry Li, Vikrant Singhal and Jonathan Ullman · 1902
Earlier work this paper cites.
“Collusion-Secure Fingerprinting for Digital Data”
Dan Boneh and James Shaw · 1905
Earlier work this paper cites.
“Probability Inequalities for Sums of Bounded Random Variables”
Wassily Hoeffding · 1963
Earlier work this paper cites.
“Our Data, Ourselves: Privacy Via Distributed Noise Generation”
Cynthia Dwork et al · 2006
Earlier work this paper cites.
“Calibrating Noise to Sensitivity in Private Data Analysis”
Cynthia Dwork, Frank McSherry, Kobbi Nissim and Adam Smith · 2006
Earlier work this paper cites.
“Optimal probabilistic fingerprint codes”
G“’abor Tardos · 2008
Earlier work this paper cites.
“Differentially Private Combinatorial Optimization”
Anupam Gupta et al · 2010
Earlier work this paper cites.
“The effectiveness of lloyd-type methods for the k-means problem”
Rafail Ostrovsky, Yuval Rabani, Leonard. Schulman and Chaitanya Swamy · 2012
Earlier work this paper cites.
“Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds”
Raef Bassily, Adam Smith and Abhradeep Thakurta · 2014
Earlier work this paper cites.
“Fingerprinting codes and the price of approximate differential privacy”
Mark Bun, Jonathan Ullman and Salil. Vadhan · 2014
Earlier work this paper cites.
“Analyze Gauss: Optimal Bounds for Privacy-preserving Principal Component Analysis”
Cynthia Dwork, Kunal Talwar, Abhradeep Thakurta and Li Zhang · 2014
Earlier work this paper cites.
“Preventing False Discovery in Interactive Data Analysis Is Hard”
Moritz Hardt and Jonathan Ullman · 2014
Earlier work this paper cites.
“Robust Traceability from Trace Amounts”
Cynthia Dwork et al · 2015
Earlier work this paper cites.
“Interactive Fingerprinting Codes and the Hardness of Preventing False Discovery”
Thomas Steinke and Jonathan Ullman · 2015
Cited alongside, same era.
“Locating a Small Cluster Privately”
Kobbi Nissim, Uri Stemmer and Salil. Vadhan · 2016
Cited alongside, same era.
“Between Pure and Approximate Differential Privacy”
Thomas Steinke and Jonathan. Ullman · 2016
Cited alongside, same era.
“Make Up Your Mind: The Price of Online Queries in Differential Privacy”
Mark Bun, Thomas Steinke and Jonathan. Ullman · 2017
Cited alongside, same era.
“Tight Lower Bounds for Differentially Private Selection”
Thomas Steinke and Jonathan Ullman · 2017
Cited alongside, same era.
“Differentially Private k-Means with Constant Multiplicative Error”
Haim Kaplan and Uri Stemmer · 2018
Cited alongside, same era.
“Differentially private sampling from distributions”
Sofya Raskhodnikova, Satchit Sivakumar, Adam Smith and Marika Swanberg · 2021
Later among the works it cites.
“Privately Learning Subspaces”
Vikrant Singhal and Thomas Steinke · 2021
Later among the works it cites.
“Privately learning subspaces”
Vikrant Singhal and Thomas Steinke · 2021
Later among the works it cites.
“Private and polynomial time algorithms for learning Gaussians and beyond”
Hassan Ashtiani and Christopher Liaw · 2022
Later among the works it cites.
“New lower bounds for private estimation and a generalized fingerprinting lemma”
Gautam Kamath, Argyris Mouzakis and Vikrant Singhal · 2022
Later among the works it cites.
“A Private and Computationally-Efficient Estimator for Unbounded Gaussians”
Gautam Kamath et al · 2022
Later among the works it cites.
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“Finite Sample Differentially Private Confidence Intervals”
Vishesh Karwa and Salil Vadhan · 2018
Cited alongside, same era.
“Clustering Algorithms for the Centralized and Local Models”
Kobbi Nissim and Uri Stemmer · 2018
Cited alongside, same era.
“Private Query Release Assisted by Public Data”
Raef Bassily et al · 2020
Cited alongside, same era.
“Differentially Private Clustering: Tight Approximation Ratios”
Badih Ghazi, Ravi Kumar and Pasin Manurangsi · 2020
Cited alongside, same era.
“Private k-Means Clustering with Stability Assumptions”
Moshe Shechner, Or Sheffet and Uri Stemmer · 2020
Cited alongside, same era.
“The cost of privacy: Optimal rates of convergence for parameter estimation with differential privacy”
T Cai, Yichen Wang and Linjun Zhang · 2021
Cited alongside, same era.
“Tight and Robust Private Mean Estimation with Few Users”
Shyam Narayanan, Vahab. Mirrokni and Hossein Esfandiari · 2022
Later among the works it cites.
“FriendlyCore: Practical Differentially Private Aggregation”
Eliad Tsfadia et al · 2022
Later among the works it cites.
“Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning”
T Cai, Yichen Wang and Linjun Zhang · 2023
Closest in time.
“The price of differential privacy under continual observation”
Palak Jain, Sofya Raskhodnikova, Satchit Sivakumar and Adam Smith · 2023
Closest in time.
“A Bias-Variance-Privacy Trilemma for Statistical Estimation”
Gautam Kamath et al · 2023
Closest in time.
“Better and Simpler Lower Bounds for Differentially Private Statistical Estimation”, 2024
Shyam Narayanan · 2024
Closest in time.
“Differentially-Private Clustering of Easy Instances”
Edith Cohen et al · 2059
Closest in time.