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Differentially private false discovery rate control

https://doi.org/10.29012/jpc.755
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/0-387-34471-3openalex-snapshot
Extreme Value Theory
inferredcites →https://doi.org/10.1007/11681878_14openalex-snapshot
Calibrating Noise to Sensitivity in Private Data Analysis
inferredcites →https://doi.org/10.1007/11761679_29openalex-snapshot
Our Data, Ourselves: Privacy Via Distributed Noise Generation
inferredcites →https://doi.org/10.1007/978-0-387-49317-6openalex-snapshot
Multiple Testing Procedures with Applications to Genomics
inferredcites →https://doi.org/10.1007/978-3-642-11799-2_26openalex-snapshot
Bounds on the Sample Complexity for Private Learning and Private Data Release
inferredcites →https://doi.org/10.1007/978-3-662-53641-4_24openalex-snapshot
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds
inferredcites →https://doi.org/10.1016/j.jbi.2014.01.008openalex-snapshot
Scalable privacy-preserving data sharing methodology for genome-wide association studies
inferredcites →https://doi.org/10.1017/9781108591034openalex-snapshot
Probability
inferredcites →https://doi.org/10.1017/s0001867800018668openalex-snapshot
On Littlewood's estimate for the binomial distribution
inferredcites →https://doi.org/10.1017/s0001867800036892openalex-snapshot
On the probability in the tail of a binomial distribution
inferredcites →https://doi.org/10.1073/pnas.1530509100openalex-snapshot
Statistical significance for genomewide studies
inferredcites →https://doi.org/10.1093/biomet/93.3.491openalex-snapshot
Adaptive linear step-up procedures that control the false discovery rate
inferredcites →https://doi.org/10.1109/focs.2007.66openalex-snapshot
Mechanism Design via Differential Privacy
inferredcites →https://doi.org/10.1109/focs.2010.12openalex-snapshot
Boosting and Differential Privacy
inferredcites →https://doi.org/10.1109/focs.2010.85openalex-snapshot
A Multiplicative Weights Mechanism for Privacy-Preserving Data Analysis
inferredcites →https://doi.org/10.1109/focs.2015.46openalex-snapshot
Robust Traceability from Trace Amounts
inferredcites →https://doi.org/10.1111/j.1467-9868.2004.00439.xopenalex-snapshot
Strong Control, Conservative Point Estimation and Simultaneous Conservative Consistency of False Discovery Rates: A Unified Approach
inferredcites →https://doi.org/10.1111/j.2517-6161.1995.tb02031.xopenalex-snapshot
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
inferredcites →https://doi.org/10.1111/rssa.12324openalex-snapshot
Differentially Private Model Selection with Penalized and Constrained Likelihood
inferredcites →https://doi.org/10.1111/rssb.12454openalex-snapshot
Gaussian Differential Privacy
inferredcites →https://doi.org/10.1126/science.aaa9375openalex-snapshot
The reusable holdout: Preserving validity in adaptive data analysis
inferredcites →https://doi.org/10.1137/15m1033587openalex-snapshot
Fingerprinting Codes and the Price of Approximate Differential Privacy
inferredcites →https://doi.org/10.1137/16m1103646openalex-snapshot
Algorithmic Stability for Adaptive Data Analysis
inferredcites →https://doi.org/10.1145/1265530.1265569openalex-snapshot
Privacy, accuracy, and consistency too
inferredcites →https://doi.org/10.1145/1536414openalex-snapshot
Proceedings of the forty-first annual ACM symposium on Theory of computing
inferredcites →https://doi.org/10.1145/1536414.1536466openalex-snapshot
Differential privacy and robust statistics
inferredcites →https://doi.org/10.1145/2450142.2450148openalex-snapshot
A learning theory approach to noninteractive database privacy
inferredcites →https://doi.org/10.1145/2976749.2978318openalex-snapshot
Deep Learning with Differential Privacy
inferredcites →https://doi.org/10.1146/annurev-genom-082410-101454openalex-snapshot
The Tension Between Data Sharing and the Protection of Privacy in Genomics Research
inferredcites →https://doi.org/10.1162/99608f92.cfc5dd25openalex-snapshot
Deep Learning with Gaussian Differential Privacy
inferredcites →https://doi.org/10.1184/r1/6586565openalex-snapshot
Differential Privacy for Functions and Functional Data
inferredcites →https://doi.org/10.1198/jasa.2009.tm08651openalex-snapshot
A Statistical Framework for Differential Privacy
inferredcites →https://doi.org/10.1214/07-aos557openalex-snapshot
Robustness of multiple testing procedures against dependence
inferredcites →https://doi.org/10.1214/07-aos569openalex-snapshot
On the false discovery rate and an asymptotically optimal rejection curve
inferredcites →https://doi.org/10.1214/07-aos586openalex-snapshot
An adaptive step-down procedure with proven FDR control under independence
inferredcites →https://doi.org/10.1214/08-aos617openalex-snapshot
On a generalized false discovery rate
inferredcites →https://doi.org/10.1214/15-aoas842openalex-snapshot
SLOPE—Adaptive variable selection via convex optimization
inferredcites →https://doi.org/10.1214/15-ejs1016openalex-snapshot
Inequalities for the false discovery rate (FDR) under dependence
inferredcites →https://doi.org/10.1214/aoms/1177699260openalex-snapshot
Some Concepts of Dependence
inferredcites →https://doi.org/10.1214/aos/1013699998openalex-snapshot
The control of the false discovery rate in multiple testing under dependency
inferredcites →https://doi.org/10.1214/aos/1015362192openalex-snapshot
Some Results on False Discovery Rate in Stepwise multiple testing procedures
inferredcites →https://doi.org/10.1214/aos/1074290335openalex-snapshot
The positive false discovery rate: a Bayesian interpretation and the q-value
inferredcites →https://doi.org/10.1371/journal.pgen.1000167openalex-snapshot
Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays
inferredcites →https://doi.org/10.1561/0400000042openalex-snapshot
The Algorithmic Foundations of Differential Privacy
inferredcites →https://doi.org/10.2307/2344365openalex-snapshot
Discrete-Parameter Martingales.
inferredcites →https://doi.org/10.2307/3315516openalex-snapshot
A generalized step‐up‐down multiple test procedure
inferredcites →https://doi.org/10.2527/jas.2012-6807openalex-snapshot
Genomewide association study of reproductive efficiency in female cattle1,2,3,4
inferredcites →https://doi.org/10.29012/jpc.v5i1.629openalex-snapshot
Privacy-Preserving Data Sharing for Genome-Wide Association Studies
inferredcites →https://doi.org/10.4230/lipics.forc.2026.4openalex-snapshot
Concentrated Differential Privacy
inferredcites →https://doi.org/10.48550/arxiv.0912.0071openalex-snapshot
Differentially Private Empirical Risk Minimization

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/sta4.70170openalex-snapshot
Differentially Private Distributed Inference Based on U‐Statistics for Massive Data
inferred← citeshttps://doi.org/10.1007/978-3-642-04898-2_248openalex-snapshot
False Discovery Rate
inferred← citeshttps://doi.org/10.1007/s10846-024-02161-9openalex-snapshot
Survey of Recent Results in Privacy-Preserving Mechanisms for Multi-Agent Systems
inferred← citeshttps://doi.org/10.1007/s11222-025-10614-wopenalex-snapshot
Distributed empirical likelihood inference with privacy guarantees
inferred← citeshttps://doi.org/10.1016/j.csda.2024.108041openalex-snapshot
Minimax rates of convergence for sliced inverse regression with differential privacy
inferred← citeshttps://doi.org/10.1016/j.jeconom.2023.05.001openalex-snapshot
Reproducibility and transparency versus privacy and confidentiality: Reflections from a data editor
inferred← citeshttps://doi.org/10.1080/01621459.2025.2555059openalex-snapshot
Differentially Private Sliced Inverse Regression: Minimax Optimality and Algorithm
inferred← citeshttps://doi.org/10.1080/01621459.2026.2644613openalex-snapshot
Adapting to Noise Tails in Private Linear Regression
inferred← citeshttps://doi.org/10.1093/jrsssb/qkag120openalex-snapshot
Knockoff inference under privacy constraints
inferred← citeshttps://doi.org/10.1109/isit54713.2023.10206942openalex-snapshot
Differentially Private Detection of Sparse Gaussian Mixtures
inferred← citeshttps://doi.org/10.1109/jsait.2024.3396079openalex-snapshot
Detection of Sparse Mixtures With Differential Privacy
inferred← citeshttps://doi.org/10.1109/mlsp52302.2021.9596470openalex-snapshot
Differentially Private Variable Selection via the Knockoff Filter
inferred← citeshttps://doi.org/10.1109/tifs.2023.3349054openalex-snapshot
Efficient Sparse Least Absolute Deviation Regression With Differential Privacy
inferred← citeshttps://doi.org/10.1214/19-aos1938openalex-snapshot
Simultaneous high-probability bounds on the false discovery proportion in structured, regression and online settings
inferred← citeshttps://doi.org/10.1214/21-aos2058openalex-snapshot
The cost of privacy: Optimal rates of convergence for parameter estimation with differential privacy
inferred← citeshttps://doi.org/10.1214/24-aos2411openalex-snapshot
Majority vote for distributed differentially private sign selection
inferred← citeshttps://doi.org/10.1214/26-ejs2588openalex-snapshot
Private Model-X Knockoffs via Johnson–Lindenstrauss transform
inferred← citeshttps://doi.org/10.1287/opre.2025.2370openalex-snapshot
Feature-Rich, Data-Private: A Sparse Learning Framework for the High-Dimensional Newsvendor
inferred← citeshttps://doi.org/10.2139/ssrn.5606310openalex-snapshot
Feature-Rich, Data-Private: A Sparse Learning Framework for the High-Dimensional Newsvendor
inferred← citeshttps://doi.org/10.48550/arxiv.1812.08965openalex-snapshot
The FDR-Linking Theorem
inferred← citeshttps://doi.org/10.48550/arxiv.1902.04495openalex-snapshot
The Cost of Privacy: Rates of Convergence for Parameter Estimation with Differential Privacy
inferred← citeshttps://doi.org/10.48550/arxiv.1908.04920openalex-snapshot
Aggregating Votes with Local Differential Privacy: Usefulness, Soundness vs. Indistinguishability
inferred← citeshttps://doi.org/10.48550/arxiv.2002.12321openalex-snapshot
PAPRIKA: Private Online False Discovery Rate Control
inferred← citeshttps://doi.org/10.48550/arxiv.2011.03900openalex-snapshot
The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax Lower Bounds
inferred← citeshttps://doi.org/10.48550/arxiv.2104.00245openalex-snapshot
High-Dimensional Differentially-Private EM Algorithm: Methods and Near-Optimal Statistical Guarantees
inferred← citeshttps://doi.org/10.48550/arxiv.2105.08233openalex-snapshot
Oneshot Differentially Private Top-k Selection
inferred← citeshttps://doi.org/10.48550/arxiv.2109.05402openalex-snapshot
Differentially Private Variable Selection via the Knockoff Filter
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