Selective inference is the problem of giving valid answers to statistica...
This paper introduces a class of asymptotically most powerful knockoff
s...
The knockoff filter of Barber and Candes (arXiv:1404.5609) is a flexible...
Despite the popularity of the false discovery rate (FDR) as an error con...
A core strength of knockoff methods is their virtually limitless
customi...
We propose a new empirical Bayes method for covariate-assisted multiple
...
We introduce a new class of methods for finite-sample false discovery ra...
A fundamental problem in high-dimensional testing is that of global null...
We consider the problem of multiple hypothesis testing when there is a
l...
Large-scale replication studies like the Reproducibility Project: Psycho...
Hypothesis testing and other statistical inference procedures are most
e...
If a document is about travel, we may expect that short snippets of the
...
Many model selection algorithms produce a path of fits specifying a sequ...
Dropout training, originally designed for deep neural networks, has been...
We propose a general framework for reduced-rank modeling of matrix-value...
For classification problems with significant class imbalance, subsamplin...