activity
20142026
most citedA Power and Prediction Analysis for Knockoffs with Lasso Statistics

26 citations · 40 across the 12 of their papers we have counts for

collaborators

14 papers

stat.ME2026

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…

math.ST2026

Posterior consistency of Pólya trees for deconvolution under the linear model

Nakul Shenoy, Asaf Weinstein

Several recent works have addressed the problem of deconvolution under a linear model, where the goal is to estimate a completely unknown from a vector of noisy observations…

math.ST2026

Empirical Bayes Variable Selection with Lasso Statistics in the AMP Framework

Lina Hidmi, Asaf Weinstein

The Lasso is one of the most ubiquitous methods for variable selection in high-dimensional linear regression and has been studied extensively under different regimes. In a particul…

math.ST2021★ 2 cited

On the Minimum Attainable Risk in Permutation Invariant Problems

Asaf Weinstein

We introduce a broad class of permutation invariant problems by extending the standard decision theoretic definition to allow also selective inference tasks, where the target is sp…

math.ST2020★ 2 cited

A Power Analysis for Model-X Knockoffs with -Regularized Statistics

Asaf Weinstein, Weijie J. Su, Małgorzata Bogdan +2

Variable selection properties of procedures utilizing penalized-likelihood estimates is a central topic in the study of high dimensional linear regression problems. Existing litera…

math.ST2019

On Optimal Solutions to Compound Statistical Decision Problems

Asaf Weinstein

In a compound decision problem, consisting of statistically independent copies of the same problem to be solved under the sum of the individual losses, any reasonable compound…