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In this work we present novel differentially private identity (goodness-of-fit) testers for natural and widely studied classes of multivariate product distributions: Gaussians in $\mathbb{R}^d$ with known covariance and product distributions over $\{\pm 1\}^{d}$.
Extension of range of functions
Edward J. McShane · 1934
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Yuri Izmailovich Ingster · 1994
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Oded Goldreich, Shafi Goldwasser, and Dana Ron · 1996
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Yuri Izmailovich Ingster · 1997
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Tuğkan Batu, Lance Fortnow, Ronitt Rubinfeld, Warren D. Smith, and Patrick White · 2000
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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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Noga Alon, Alexandr Andoni, Tali Kaufman, Kevin Matulef, Ronitt Rubinfeld, and Ning Xie · 2007
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Smooth sensitivity and sampling in private data analysis
Kobbi Nissim, Sofya Raskhodnikova, and Adam Smith · 2007
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Liam Paninski · 2008
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Differential privacy for clinical trial data: Preliminary evaluations
Duy Vu and Aleksandra Slavković · 2009
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Adam Smith · 2011
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Testing symmetric properties of distributions
Paul Valiant · 2011
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Taming big probability distributions
Ronitt Rubinfeld · 2012
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Differentially private data analysis of social networks via restricted sensitivity
Jeremiah Blocki, Avrim Blum, Anupam Datta, and Or Sheffet · 2013
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Local privacy and statistical minimax rates
John C. Duchi, Michael I. Jordan, and Martin J. Wainwright · 2013
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Analyzing graphs with node differential privacy
Shiva Prasad Kasiviswanathan, Kobbi Nissim, Sofya Raskhodnikova, and Adam Smith · 2013
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Testing properties of collections of distributions
Reut Levi, Dana Ron, and Ronitt Rubinfeld · 2013
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Privacy-preserving data sharing for genome-wide association studies
Caroline Uhler, Aleksandra Slavković, and Stephen E. Fienberg · 2013
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Impossibility of differentially private universally optimal mechanisms
Hai Brenner and Kobbi Nissim · 2014
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Fingerprinting codes and the price of approximate differential privacy
Mark Bun, Jonathan Ullman, and Salil Vadhan · 2014
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Optimal algorithms for testing closeness of discrete distributions
Siu On Chan, Ilias Diakonikolas, Gregory Valiant, and Paul Valiant · 2014
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The algorithmic foundations of differential privacy
Cynthia Dwork and Aaron Roth · 2014
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RAPPOR: Randomized aggregatable privacy-preserving ordinal response
Úlfar Erlingsson, Vasyl Pihur, and Aleksandra Korolova · 2014
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Testing non-uniform k-wise independent distributions over product spaces
Ronitt Rubinfeld and Ning Xie · 2014
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An automatic inequality prover and instance optimal identity testing
Gregory Valiant and Paul Valiant · 2014
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Optimal testing for properties of distributions
Jayadev Acharya, Constantinos Daskalakis, and Gautam Kamath · 2015
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Differentially private release and learning of threshold functions
Mark Bun, Kobbi Nissim, Uri Stemmer, and Salil Vadhan · 2015
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Bhaswar Bhattacharya and Gregory Valiant · 2015
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Clément L. Canonne · 2015
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Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Aaron Roth · 2015
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Differentially private learning of structured discrete distributions
Ilias Diakonikolas, Moritz Hardt, and Ludwig Schmidt · 2015
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Testing identity of structured distributions
Ilias Diakonikolas, Daniel M. Kane, and Vladimir Nikishkin · 2015
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Revisiting differentially private hypothesis tests for categorical data
Differentially private testing of identity and closeness of discrete distributions
Jayadev Acharya, Ziteng Sun, and Huanyu Zhang · 2018
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Private algorithms can always be extended
Christian Borgs, Jennifer Chayes, Adam Smith, and Ilias Zadik · 2018
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Revealing network structure, confidentially: Improved rates for node-private graphon estimation
Christian Borgs, Jennifer Chayes, Adam Smith, and Ilias Zadik · 2018
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Hypothesis testing for high-dimensional multinomials: A selective review
Sivaraman Balakrishnan and Larry Wasserman · 2018
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Differentially private ANOVA testing
Zachary Campbell, Andrew Bray, Anna Ritz, and Adam Groce · 2018
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Yue Wang, Jaewoo Lee, and Daniel Kifer · 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: Simplifications, extensions, and lower bounds
Mark Bun and Thomas Steinke · 2016
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Clément L. Canonne, Ilias Diakonikolas, Themis Gouleakis, and Ronitt Rubinfeld · 2016
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A new approach for testing properties of discrete distributions
Ilias Diakonikolas and Daniel M. Kane · 2016
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Concentrated differential privacy
Cynthia Dwork and Guy N. Rothblum · 2016
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Differentially private chi-squared hypothesis testing: Goodness of fit and independence testing
Marco Gaboardi, Hyun-Woo Lim, Ryan M. Rogers, and Salil P. Vadhan · 2016
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Clément L. Canonne, Ilias Diakonikolas, Daniel M. Kane, and Alistair Stewart · 2018
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Differentially private change-point detection
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Constantinos Daskalakis, Nishanth Dikkala, and Gautam Kamath · 2018
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Which distribution distances are sublinearly testable?
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The total variation distance between high-dimensional Gaussians
Luc Devroye, Abbas Mehrabian, and Tommy Reddad · 2018
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The right complexity measure in locally private estimation: It is not the fisher information
John C. Duchi and Feng Ruan · 2018
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Concentration inequalities for polynomials of contracting Ising models
Reza Gheissari, Eyal Lubetzky, and Yuval Peres · 2018
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Local private hypothesis testing: Chi-square tests
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Modern Challenges in Distribution Testing
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Finite sample differentially private confidence intervals
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Locally private hypothesis testing
Or Sheffet · 2018
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Statistical approximating distributions under differential privacy
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Min Ye and Alexander Barg · 2018
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Test without trust: Optimal locally private distribution testing
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Individual sensitivity preprocessing for data privacy
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