Defines threshold breakdown point and m-sensitivity for M-estimators, derives their properties, extends to hypothesis testing, and supplies consistency, asymptotic normality, and multiplier bootstrap results.
Propose, test, re- lease: Differentially private estimation with high probability
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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Efficient PTR replaces exact insensitive sets and Hellinger distances with simpler subsets and Lipschitz lower bounds to achieve minimax-optimal accuracy for DP Bayes classification, linear regression, and nonparametric regression.
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The Threshold Breakdown Point
Defines threshold breakdown point and m-sensitivity for M-estimators, derives their properties, extends to hypothesis testing, and supplies consistency, asymptotic normality, and multiplier bootstrap results.
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Efficient Proposal-Test-Release for Minimax Optimal Estimation
Efficient PTR replaces exact insensitive sets and Hellinger distances with simpler subsets and Lipschitz lower bounds to achieve minimax-optimal accuracy for DP Bayes classification, linear regression, and nonparametric regression.