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In this paper, we introduce a notion of algorithmic stability called typical stability.
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
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith · 2006
Earlier work this paper cites.
Differential privacy
Cynthia Dwork · 2006
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.
A learning theory approach to non-interactive database privacy
Avrim Blum, Katrina Ligett, and Aaron Roth · 2008
Earlier work this paper cites.
Boosting and differential privacy
Cynthia Dwork, Guy N. Rothblum, and Salil P. Vadhan · 2010
Earlier work this paper cites.
Collective stability in structured prediction: Collective stability in structured prediction: Generalization from one example
Ben London, Bert Huang, Ben Taskar, and Lise Getoor · 2013
Earlier work this paper cites.
The geometry of di erential privacy: The sparse and approximate cases
Aleksandar Nikolov, Kunal Talwar, and Li Zhang · 2013
Cited alongside, same era.
The algorithmic foundations of differential privacy
Cynthia Dwork and Aaron Roth · 2014
Cited alongside, same era.
On the ‘semantics’ of differential privacy: A bayesian formulation
Shiva P. Kasiviswanathan and Adam Smith · 2014
Cited alongside, same era.
Generalization in adaptive data analysis and holdout reuse
Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Aaron Roth · 2015
Cited alongside, same era.
Preserving statistical validity in adaptive data analysis
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
Controlling bias in adaptive data analysis using information theory
Daniel Russo and James Zhou · 2015
Later among the works it cites.
Algorithmic stability for adaptive data analysis
Raef Bassily, Kobbi Nissim, Adam Smith, Uri Stemmer, Thomas Steinke, and Jonathan Ullman · 2016
Closest in time.
Adaptive learning with robust generalization guarantees
Rachel Cummings, Katrina Ligett, Kobbi Nissim, Aaron Roth, and Zhiwei Steven Wu · 2016
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Concentrated differential privacy
Cynthia Dwork and Guy Rothblum · 2016
Closest in time.
Max-information, differential privacy, and post-selection hypothesis testing
Ryan Rogers, Aaron Roth, Adam Smith, and Om Thakkar · 2016
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Cited alongside, same era.
Closest in time.
A minimax theory for adaptive data analysis
Yu-Xiang Wang, Jing Lei, and Stephen E. Fienberg · 2016
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