3k citations · 24.2k across the 299 of their papers we have counts for
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Asynchronous Online Testing of Multiple Hypotheses
Tijana Zrnic, Aaditya Ramdas, Michael I. Jordan
We consider the problem of asynchronous online testing, aimed at providing control of the false discovery rate (FDR) during a continual stream of data collection and testing, where…
Evaluating Sensitivity to the Stick-Breaking Prior in Bayesian Nonparametrics
Ryan Giordano, Runjing Liu, Michael I. Jordan +1
Bayesian models based on the Dirichlet process and other stick-breaking priors have been proposed as core ingredients for clustering, topic modeling, and other unsupervised learnin…
A Swiss Army Infinitesimal Jackknife
Ryan Giordano, Will Stephenson, Runjing Liu +2
The error or variability of machine learning algorithms is often assessed by repeatedly re-fitting a model with different weighted versions of the observed data. The ubiquitous too…
SAFFRON: an adaptive algorithm for online control of the false discovery rate
Aaditya Ramdas, Tijana Zrnic, Martin Wainwright +1
In the online false discovery rate (FDR) problem, one observes a possibly infinite sequence of -values , each testing a different null hypothesis, and an algorith…