The right complexity measure in locally private estimation: it is not the Fisher information
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Publication:6151956
DOI10.1214/22-aos2227arXiv1806.05756OpenAlexW2808701946MaRDI QIDQ6151956
Publication date: 11 March 2024
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1806.05756
\(L^1\) informationlocal minimax complexitylocally private estimationstrong data processing inequalities
Cites Work
- Unnamed Item
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- Asymptotic methods in statistical decision theory
- Estimating a bounded normal mean
- Geometrizing rates of convergence. II
- Geometrizing rates of convergence. III
- Pointwise and sup-norm sharp adaptive estimation of functions on the Sobolev classes
- A constrained risk inequality with applications to nonparametric functional estimation
- On contraction properties of Markov kernels
- Asymptotics in statistics. Some basic concepts.
- Geometrizing rates of convergence under local differential privacy constraints
- The privacy blanket of the shuffle model
- On the f-divergence and singularity of probability measures
- Asymptotic optimality in stochastic optimization
- On the geometry of differential privacy
- Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias
- Rényi Divergence and Kullback-Leibler Divergence
- Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds
- The Algorithmic Foundations of Differential Privacy
- A Framework For Estimation Of Convex Functions
- On Divergences and Informations in Statistics and Information Theory
- Graphical Models, Exponential Families, and Variational Inference
- Acceleration of Stochastic Approximation by Averaging
- Respondent Jeopardy and Optimal Designs in Randomized Response Models
- Asymptotic Statistics
- Minimax Optimal Procedures for Locally Private Estimation
- [https://portal.mardi4nfdi.de/wiki/Publication:4743580 Approximation dans les espaces m�triques et th�orie de l'estimation]
- Panning for Gold: ‘Model-X’ Knockoffs for High Dimensional Controlled Variable Selection
- Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity
- A Statistical Framework for Differential Privacy
- Information-Theoretic Lower Bounds on the Oracle Complexity of Stochastic Convex Optimization
- Testing Statistical Hypotheses
- Elements of Information Theory
- Theory of Cryptography
- Introduction to nonparametric estimation
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