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We design a general framework for answering adaptive statistical queries that focuses on providing explicit confidence intervals along with point estimates.
Entropy and Information Theory
Robert M. Gray · 1990
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Our data, ourselves: Privacy via distributed noise generation
Cynthia Dwork, Krishnaram Kenthapadi, Frank McSherry, Ilya Mironov, and Moni Naor · 2006
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Boosting and differential privacy
Cynthia Dwork, Guy N. Rothblum, and Salil P. Vadhan · 2010
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Fingerprinting codes and the price of approximate differential privacy
Mark Bun, Jonathan Ullman, and Salil P. Vadhan · 2014
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The statistical crisis in science
Andrew Gelman and Eric Loken · 2014
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Preventing false discovery in interactive data analysis is hard
Moritz Hardt and Jonathan Ullman · 2014
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On the ‘Semantics’ of Differential Privacy: A Bayesian Formulation
S.P. Kasiviswanathan and A. Smith · 2014
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How much does your data exploration overfit? Controlling bias via information usage
D. Russo and J. Zou · 2015
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Interactive fingerprinting codes and the hardness of preventing false discovery
Thomas Steinke and Jonathan Ullman · 2015
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Algorithmic stability for adaptive data analysis
Raef Bassily, Kobbi Nissim, Adam Smith, Thomas Steinke, Uri Stemmer, and Jonathan Ullman · 2016
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Concentrated differential privacy
Cynthia Dwork and Guy N. Rothblum · 2016
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Max-information, differential privacy, and post-selection hypothesis testing
Ryan Rogers, Aaron Roth, Adam Smith, and Om Thakkar · 2016
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Controlling bias in adaptive data analysis using information theory
The composition theorem for differential privacy
Peter Kairouz, Sewoong Oh, and Pramod Viswanath · 2017
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Information-theoretic analysis of generalization capability of learning algorithms
Aolin Xu and Maxim Raginsky · 2017
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Test data reuse for evaluation of adaptive machine learning algorithms: over-fitting to a fixed’test’dataset and a potential solution
Alexej Gossmann, Aria Pezeshk, and Berkman Sahiner · 2018
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A new analysis of differential privacy’s generalization guarantees, 2019
Christopher Jung, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, and Moshe Shenfeld · 2019
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Model similarity mitigates test set overuse
Horia Mania, John Miller, Ludwig Schmidt, Moritz Hardt, and Benjamin Recht · 2019
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Daniel Russo and James Zou · 2016
Cited alongside, same era.
Generalization for adaptively-chosen estimators via stable median
Vitaly Feldman and Thomas Steinke · 2017
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Concentrated differential privacy: Simplifications, extensions, and lower bounds
Mark Bun and Thomas Steinke
Cited in the paper.
Concentrated differential privacy: Simplifications, extensions, and lower bounds
Mark Bun and Thomas Steinke
Cited in the paper.
Calibrating noise to sensitivity in private data analysis
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith
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Generalization in adaptive data analysis and holdout reuse
Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toni Pitassi, Omer Reingold, and Aaron Roth
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The reusable holdout: Preserving validity in adaptive data analysis
Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Aaron Roth
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Repository for empirical adaptive data analysis
Ryan Rogers, Aaron Roth, Adam Smith, Nathan Srebro, Om Thakkar, and Blake Woodworth · 2019
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Natural analysts in adaptive data analysis
Tijana Zrnic and Moritz Hardt · 2019
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