7 citations · 17 across the 7 of their papers we have counts for
9 papers
Estimating the local false discovery rate under an unknown symmetric null
Daniel Xiang, William Fithian, Nikolaos Ignatiadis +2
This paper is concerned with estimating the local false discovery rate (lfdr) in a two-groups model where the only assumption regarding the null distribution is symmetry about zero…
Incentive-Theoretic Bayesian Inference for Collaborative Science
Stephen Bates, Michael I. Jordan, Michael Sklar +1
Contemporary scientific research is a distributed, collaborative endeavor, carried out by teams of researchers, regulatory institutions, funding agencies, commercial partners, and…
Bagging Provides Assumption-free Stability
Jake A. Soloff, Rina Foygel Barber, Rebecca Willett
Bagging is an important technique for stabilizing machine learning models. In this paper, we derive a finite-sample guarantee on the stability of bagging for any model. Our result…
The edge of discovery: Controlling the local false discovery rate at the margin
Jake A. Soloff, Daniel Xiang, William Fithian
Despite the popularity of the false discovery rate (FDR) as an error control metric for large-scale multiple testing, its close Bayesian counterpart the local false discovery rate…
Principal-Agent Hypothesis Testing
Stephen Bates, Michael I. Jordan, Michael Sklar +1
Consider the relationship between a regulator (the principal) and an experimenter (the agent) such as a pharmaceutical company. The pharmaceutical company wishes to sell a drug for…
Multivariate, Heteroscedastic Empirical Bayes via Nonparametric Maximum Likelihood
Jake A. Soloff, Adityanand Guntuboyina, Bodhisattva Sen
Multivariate, heteroscedastic errors complicate statistical inference in many large-scale denoising problems. Empirical Bayes is attractive in such settings, but standard parametri…