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Adaptivity is an important feature of data analysis---the choice of questions to ask about a dataset often depends on previous interactions with the same dataset.
Teoria statistica delle classi e calcolo delle probabilita
Carlo Emilio Bonferroni · 1936
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Multiple comparisons among means
Olive Jean Dunn · 1961
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Distribution-free inequalities for the deleted and holdout error estimates
Luc Devroye and Terry J. Wagner · 1979
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Distribution-free performance bounds for potential function rules
Luc Devroye and Terry J. Wagner · 1979
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Efficient noise-tolerant learning from statistical queries
Michael J. Kearns · 1993
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Controlling the false discovery rate: a practical and powerful approach to multiple testing
Yoav Benjamini and Yosef Hochberg · 1995
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Algorithmic stability and sanity-check bounds for leave-one-out cross-validation
Michael J. Kearns and Dana Ron · 1999
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Stability and generalization
Olivier Bousquet and André Elisseeff · 2002
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Revealing information while preserving privacy
Irit Dinur and Kobbi Nissim · 2003
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Why most published research findings are false
John P. A. Ioannidis · 2005
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Calibrating noise to sensitivity in private data analysis
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith · 2006
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Differential privacy
Cynthia Dwork · 2006
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Frank McSherry and Kunal Talwar · 2007
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Cynthia Dwork, Guy N. Rothblum, and Salil P. Vadhan · 2010
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A multiplicative weights mechanism for privacy-preserving data analysis
Moritz Hardt and Guy Rothblum · 2010
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Interactive privacy via the median mechanism
Aaron Roth and Tim Roughgarden · 2010
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Learnability, stability and uniform convergence
Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, and Karthik Sridharan · 2010
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Answering n 2+o(1)
Differential privacy for measure concentration
Frank McSherry · 2014
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The ladder: A reliable leaderboard for machine learning competitions
Avrim Blum and Moritz Hardt · 2015
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More general queries and less generalization error in adaptive data analysis
Raef Bassily, Adam Smith, Thomas Steinke, and Jonathan Ullman · 2015
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Generalization in adaptive data analysis and holdout reuse
Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Aaron Roth · 2015
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Preserving statistical validity in adaptive data analysis
Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Aaron Roth · 2015
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Jonathan Ullman · 2013
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Private empirical risk minimization: Efficient algorithms and tight error bounds
Raef Bassily, Adam Smith, and Abhradeep Thakurta · 2014
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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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Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Aaron Roth · 2015
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Kobbi Nissim and Uri Stemmer · 2015
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Thomas Steinke and Jonathan Ullman · 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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Private multiplicative weights beyond linear queries
Jonathan Ullman · 2015
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