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We provide improved differentially private algorithms for identity testing of high-dimensional distributions.
The generalization of student’s ratio
Harold Hotelling · 1931
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Concentration Inequalities: A Nonasymptotic Theory of Independence
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Optimal hypothesis testing for high dimensional covariance matrices
T. Tony Cai and Zongming Ma · 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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Privacy-preserving data sharing for genome-wide association studies
Caroline Uhler, Aleksandra B. Slavkovic, and Stephen E. Fienberg · 2013
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Úlfar Erlingsson, Vasyl Pihur, and Aleksandra Korolova · 2014
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Confidence intervals and hypothesis testing for high-dimensional regression
Adel Javanmard and Andrea Montanari · 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 hypothesis testing, revisited
Yue Wang, Jaewoo Lee, and Daniel Kifer · 2015
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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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Bryan Cai, Constantinos Daskalakis, and Gautam Kamath · 2017
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Jayadev Acharya, Clément L. Canonne, Cody Freitag, and Himanshu Tyagi · 2019
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Private testing of distributions via sample permutations
Maryam Aliakbarpour, Ilias Diakonikolas, Daniel Kane, and Ronitt Rubinfeld · 2019
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Private hypothesis selection
Mark Bun, Gautam Kamath, Thomas Steinke, and Zhiwei Steven Wu · 2019
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The structure of optimal private tests for simple hypotheses
Clément L. Canonne, Gautam Kamath, Audra McMillan, Adam D. Smith, and Jonathan R. Ullman · 2019
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Differentially private nonparametric hypothesis testing
Simon Couch, Zeki Kazan, Kaiyan Shi, Andrew Bray, and Adam Groce · 2019
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Privately learning high-dimensional distributions
Gautam Kamath, Jerry Li, Vikrant Singhal, and Jonathan R. Ullman · 2019
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Aref N. Dajani, Amy D. Lauger, Phyllis E. Singer, Daniel Kifer, Jerome P. Reiter, Ashwin Machanavajjhala, Simson L. Garfinkel, Scot A. Dahl, Matthew Graham, Vishesh Karwa, Hang Kim, Philip Lelerc, Ian M. Schmutte, William N. Sexton, Lars Vilhuber, and John M. Abowd · 2017
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Square hellinger subadditivity for bayesian networks and its applications to identity testing
Constantinos Daskalakis and Qinxuan Pan · 2017
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Differentially private chi-squared test by unit circle mechanism
Kazuya Kakizaki, Kazuto Fukuchi, and Jun Sakuma · 2017
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A new class of private chi-square hypothesis tests
Ryan Rogers and Daniel Kifer · 2017
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Learning with privacy at scale
Apple Differential Privacy Team · 2017
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Learning and testing causal models with interventions
Jayadev Acharya, Arnab Bhattacharyya, Constantinos Daskalakis, and Saravanan Kandasamy · 2018
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Differentially private identity and equivalence testing of discrete distributions
Maryam Aliakbarpour, Ilias Diakonikolas, and Ronitt Rubinfeld · 2018
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Differentially private algorithms for learning mixtures of separated gaussians
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Improved differentially private analysis of variance
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Lower bounds for testing graphical models: Colorings and antiferromagnetic ising models
Ivona Bezáková, Antonio Blanca, Zongchen Chen, Daniel Stefankovic, and Eric Vigoda · 2020
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Coinpress: Practical private mean and covariance estimation
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A survey on distribution testing. Your data is big. But is it blue?
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Testing bayesian networks
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Private identity testing for high-dimensional distributions
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Locally private hypothesis selection
Sivakanth Gopi, Gautam Kamath, Janardhan Kulkarni, Aleksandar Nikolov, Zhiwei Steven Wu, and Huanyu Zhang · 2020
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Private mean estimation of heavy-tailed distributions
Gautam Kamath, Vikrant Singhal, and Jonathan R. Ullman · 2020
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The cost of privacy: Optimal rates of convergence for parameter estimation with differential privacy
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The sample complexity of robust covariance testing
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Differentially private high dimensional sparse covariance matrix estimation
Di Wang and Jinhui Xu · 2021
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Minimax optimal goodness-of-fit testing for densities and multinomials under a local differential privacy constraint
Joseph Lam-Weil, Béatrice Laurent, and Jean-Michel Loubes · 2022
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