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pro vyhledávání: '"Bray, Andrew P."'
We present a generic framework for creating differentially private versions of any hypothesis test in a black-box way. We analyze the resulting tests analytically and experimentally. Most crucially, we show good practical performance for small data s
Externí odkaz:
http://arxiv.org/abs/2302.04260
Confidence intervals for the population mean of normally distributed data are some of the most standard statistical outputs one might want from a database. In this work we give practical differentially private algorithms for this task. We provide fiv
Externí odkaz:
http://arxiv.org/abs/2001.02285
Hypothesis tests are a crucial statistical tool for data mining and are the workhorse of scientific research in many fields. Here we study differentially private tests of independence between a categorical and a continuous variable. We take as our st
Externí odkaz:
http://arxiv.org/abs/1903.09364
Hypothesis testing is one of the most common types of data analysis and forms the backbone of scientific research in many disciplines. Analysis of variance (ANOVA) in particular is used to detect dependence between a categorical and a numerical varia
Externí odkaz:
http://arxiv.org/abs/1903.00534
Hypothesis tests are a crucial statistical tool for data mining and are the workhorse of scientific research in many fields. Here we present a differentially private analogue of the classic Wilcoxon signed-rank hypothesis test, which is used when com
Externí odkaz:
http://arxiv.org/abs/1809.01635
Autor:
De Veaux, Richard, Agarwal, Mahesh, Averett, Maia, Baumer, Benjamin, Bray, Andrew, Bressoud, Thomas, Bryant, Lance, Cheng, Lei, Francis, Amanda, Gould, Robert, Kim, Albert Y., Kretchmar, Matt, Lu, Qin, Moskol, Ann, Nolan, Deborah, Pelayo, Roberto, Raleigh, Sean, Sethi, Ricky J., Sondjaja, Mutiara, Tiruviluamala, Neelesh, Uhlig, Paul, Washington, Talitha, Wesley, Curtis, White, David, Ye, Ping
Publikováno v:
Annual Review of Statistics, Volume 4 (2017), 15-30
The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in Data Science. The group consisted of 25 undergraduate faculty from a variety of institutions in th
Externí odkaz:
http://arxiv.org/abs/1801.06814
Modern society generates an incredible amount of data about individuals, and releasing summary statistics about this data in a manner that provably protects individual privacy would offer a valuable resource for researchers in many fields. We present
Externí odkaz:
http://arxiv.org/abs/1711.01335
Akademický článek
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Akademický článek
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Publikováno v:
Annals of Applied Statistics 2014, Vol. 8, No. 4, 2247-2267
Many point process models have been proposed for describing and forecasting earthquake occurrences in seismically active zones such as California, but the problem of how best to compare and evaluate the goodness of fit of such models remains open. Ex
Externí odkaz:
http://arxiv.org/abs/1501.06387