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Datasets are often reused to perform multiple statistical analyses in an adaptive way, in which each analysis may depend on the outcomes of previous analyses on the same dataset.
“Efficient noise-tolerant Learning from statistical queries”
M. Kearns · 1998
Earlier work this paper cites.
“Our data, ourselves: Privacy via distributed noise generation”
Cynthia Dwork, Krishnaram Kenthapadi, Frank McSherry, Ilya Mironov and Moni Naor · 2006
Earlier work this paper cites.
“Calibrating noise to sensitivity in private data analysis”
C. Dwork, F. McSherry, K. Nissim and A. Smith · 2006
Earlier work this paper cites.
“Mechanism Design via Differential Privacy”
Frank McSherry and Kunal Talwar · 2007
Earlier work this paper cites.
“Smooth sensitivity and sampling in private data analysis”
Kobbi Nissim, Sofya Raskhodnikova and Adam. Smith · 2007
Earlier work this paper cites.
“Differential Privacy and Robust Statistics”
Cynthia Dwork and Jing Lei · 2009
Earlier work this paper cites.
“On the complexity of differentially private data release: efficient algorithms and hardness results”
C. Dwork, M. Naor, O. Reingold, G. Rothblum and S. Vadhan · 2009
Earlier work this paper cites.
“Boosting and Differential Privacy”
Cynthia Dwork, Guy. Rothblum and Salil. Vadhan · 2010
Earlier work this paper cites.
“A Multiplicative Weights Mechanism for Privacy-Preserving Data Analysis”
M. Hardt and G. Rothblum · 2010
Earlier work this paper cites.
“Algorithmic Challenges in Data Privacy. HW 1”, http://www.cse.psu.edu/ads22/privacy598/handouts/hw1.pdf , 2010
Sofya Raskhodnikova and Adam. Smith · 2010
Earlier work this paper cites.
“Privacy-preserving statistical estimation with optimal convergence rates”
Adam Smith · 2011
Cited alongside, same era.
“Preserving Statistical Validity in Adaptive Data Analysis” Extended abstract in STOC 2015
Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold and Aaron Roth · 2014
Cited alongside, same era.
“The Algorithmic Foundations of Differential Privacy”
Cynthia Dwork and Aaron Roth · 2014
Cited alongside, same era.
“Preventing False Discovery in Interactive Data Analysis Is Hard”
M. Hardt and J. Ullman · 2014
Cited alongside, same era.
“Topics In Cryptography and Privacy - Differential Privacy. HW 1”, http://isites.harvard.edu/fs/docs/icb.topic1475289.files/hwk1-kobbi.pdf , 2014
Kobbi Nissim and Or Sheffet · 2014
Cited alongside, same era.
“Concentrated differential privacy: Simplifications, extensions, and lower bounds”
Mark Bun and Thomas Steinke · 2016
Later among the works it cites.
“Dealing with Range Anxiety in Mean Estimation via Statistical Queries”
Vitaly Feldman · 2016
Later among the works it cites.
“Max-information, differential privacy, and post-selection hypothesis testing”
Ryan Rogers, Aaron Roth, Adam Smith and Om Thakkar · 2016
Later among the works it cites.
“Information-theoretic analysis of stability and bias of learning algorithms”
Maxim Raginsky, Alexander Rakhlin, Matthew Tsao, Yihong Wu and Aolin Xu · 2016
Later among the works it cites.
“Controlling bias in adaptive data analysis using information theory”
Daniel Russo and James Zou · 2016
Later among the works it cites.
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“Differentially private release and learning of threshold functions”
Mark Bun, Kobbi Nissim, Uri Stemmer and Salil Vadhan · 2015
Cited alongside, same era.
“Generalization in Adaptive Data Analysis and Holdout Reuse” Extended abstract in NIPS 2015
Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold and Aaron Roth · 2015
Cited alongside, same era.
“The reusable holdout: Preserving validity in adaptive data analysis”
Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold and Aaron Roth · 2015
Cited alongside, same era.
“Interactive Fingerprinting Codes and the Hardness of Preventing False Discovery”
Thomas Steinke and Jonathan Ullman · 2015
Cited alongside, same era.
“Algorithmic stability for adaptive data analysis”
Raef Bassily, Kobbi Nissim, Adam. Smith, Thomas Steinke, Uri Stemmer and Jonathan Ullman · 2016
Cited alongside, same era.
Thomas Steinke and Jonathan Ullman · 2016
Later among the works it cites.
“Make up your mind: The price of online queries in differential privacy”
Mark Bun, Thomas Steinke and Jonathan Ullman · 2017
Closest in time.
“Concentration Bounds for High Sensitivity Functions Through Differential Privacy”
Kobbi Nissim and Uri Stemmer · 2017
Closest in time.
“Subgaussian Tail Bounds via Stability Arguments”
Thomas Steinke and Jonathan Ullman · 2017
Closest in time.
“Information-theoretic analysis of generalization capability of learning algorithms”
Aolin Xu and Maxim Raginsky · 2017
Closest in time.