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Traditional statistical theory assumes that the analysis to be performed on a given data set is selected independently of the data themselves.
Distribution-free performance bounds for potential function rules
L. Devroye and T. Wagner · 1979
Earlier work this paper cites.
Relating data compression and learnability
N. Littlestone and M. Warmuth · 1986
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The impact of model selection on inference in linear regression
C. M. Hurvich and C.-L. Tsai · 1990
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Effects of model selection on inference
B. M. Pötscher · 1991
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Efficient noise-tolerant learning from statistical queries
M. Kearns · 1998
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Stability and generalization
O. Bousquet and A. Elisseeff · 2002
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Smooth Rényi entropy and applications
R. Renner and S. Wolf · 2004
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Simple and tight bounds for information reconciliation and privacy amplification
R. Renner and S. Wolf · 2005
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Fuzzy extractors: How to generate strong keys from biometrics and other noisy data
Y. Dodis, R. Ostrovsky, L. Reyzin, and A. Smith · 2008
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Boosting and differential privacy
C. Dwork, G. N. Rothblum, and S. Vadhan · 2010
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Duality between smooth min- and max-entropies
M. Tomamichel, R. Colbeck, and R. Renner · 2010
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Measuring information leakage using generalized gain functions
M. S. Alvim, K. Chatzikokolakis, C. Palamidessi, and G. Smith · 2012
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Valid post-selection inference
R. Berk, L. Brown, A. Buja, K. Zhang, and L. Zhao · 2013
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Min-entropy as a resource
B. Espinoza and G. Smith · 2013
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The composition theorem for differential privacy
S. Oh and P. Viswanath · 2013
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Chain rules for smooth min- and max-entropies
A. Vitanov, F. Dupuis, M. Tomamichel, and R. Renner · 2013
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Additive and multiplicative notions of leakage, and their capacities
M. S. Alvim, K. Chatzikokolakis, A. McIver, C. Morgan, C. Palamidessi, and G. Smith · 2014
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Private empirical risk minimization: Efficient algorithms and tight error bounds
R. Bassily, A. Smith, and A. Thakurta · 2014
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Smooth max-information as one-shot generalization for mutual information
N. Ciganovic, N. J. Beaudry, and R. Renner · 2014
Interactive fingerprinting codes and the hardness of preventing false discovery
T. Steinke and J. Ullman · 2015
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Selective inference with a randomized response
X. Tian and J. E. Taylor · 2015
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Axioms for information leakage
M. S. Alvim, K. Chatzikokolakis, A. McIver, C. Morgan, C. Palamidessi, and G. Smith · 2016
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R. Bassily and Y. Freund · 2016
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Algorithmic stability for adaptive data analysis
R. Bassily, K. Nissim, A. Smith, T. Steinke, U. Stemmer, and J. Ullman · 2016
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Concentrated differential privacy: Simplifications, extensions, and lower bounds
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Estimation and accuracy after model selection
B. Efron · 2014
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Optimal inference after model selection
W. Fithian, D. Sun, and J. Taylor · 2014
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The statistical crisis in science
A. Gelman and E. Loken · 2014
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Preventing false discovery in interactive data analysis is hard
M. Hardt and J. Ullman · 2014
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A significance test for the lasso
R. Lockhart, J. Taylor, R. J. Tibshirani, and R. Tibshirani · 2014
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The ladder: A reliable leaderboard for machine learning competitions
A. Blum and M. Hardt · 2015
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M. Bun and T. Steinke · 2016
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Adaptive learning with robust generalization guarantees
R. Cummings, K. Ligett, K. Nissim, A. Roth, and Z. S. Wu · 2016
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Selective sampling after solving a convex problem
X. T. Harris, S. Panigrahi, J. Markovic, N. Bi, and J. Taylor · 2016
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Exact post-selection inference, with application to the lasso
J. D. Lee, D. L. Sun, Y. Sun, and J. E. Taylor · 2016
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Max-information, differential privacy, and post-selection hypothesis testing
R. Rogers, A. Roth, A. Smith, and O. Thakkar · 2016
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Controlling bias in adaptive data analysis using information theory
D. Russo and J. Zou · 2016
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Magic: a general, powerful and tractable method for selective inference
X. Tian, N. Bi, and J. Taylor · 2016
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