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12/18/2022
Locally Simultaneous Inference
Selective inference is the problem of giving valid answers to statistica...
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12/17/2022
Asymptotically Optimal Knockoff Statistics via the Masked Likelihood Ratio
This paper introduces a class of asymptotically most powerful knockoff s...
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08/19/2022
Improving knockoffs with conditional calibration
The knockoff filter of Barber and Candes (arXiv:1404.5609) is a flexible...
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07/15/2022
The edge of discovery: Controlling the local false discovery rate at the margin
Despite the popularity of the false discovery rate (FDR) as an error con...
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06/30/2021
Whiteout: when do fixed-X knockoffs fail?
A core strength of knockoff methods is their virtually limitless customi...
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06/30/2021
AdaPT-GMM: Powerful and robust covariate-assisted multiple testing
We propose a new empirical Bayes method for covariate-assisted multiple ...
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07/20/2020
Conditional calibration for false discovery rate control under dependence
We introduce a new class of methods for finite-sample false discovery ra...
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06/19/2020
Optimality of the max test for detecting sparse signals with Gaussian or heavier tail
A fundamental problem in high-dimensional testing is that of global null...
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11/20/2019
Smoothed Nested Testing on Directed Acyclic Graphs
We consider the problem of multiple hypothesis testing when there is a l...
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03/20/2019
Statistical Methods for Replicability Assessment
Large-scale replication studies like the Reproducibility Project: Psycho...
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11/27/2017
Family learning: nonparametric statistical inference with parametric efficiency
Hypothesis testing and other statistical inference procedures are most e...
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03/21/2016
Data Augmentation via Levy Processes
If a document is about travel, we may expect that short snippets of the ...
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12/08/2015
Selective Sequential Model Selection
Many model selection algorithms produce a path of fits specifying a sequ...
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07/11/2014
Altitude Training: Strong Bounds for Single-Layer Dropout
Dropout training, originally designed for deep neural networks, has been...
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08/20/2013
Flexible Low-Rank Statistical Modeling with Side Information
We propose a general framework for reduced-rank modeling of matrix-value...
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06/16/2013
