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20152026
most citedA Power and Prediction Analysis for Knockoffs with Lasso Statistics

26 citations · 54 across the 24 of their papers we have counts for

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Showing 2018Show all

8 papers · 1 filter

stat.ME2018

On the Construction of Knockoffs in Case-Control Studies

Rina Foygel Barber, Emmanuel Candes

Consider a case-control study in which we have a random sample, constructed in such a way that the proportion of cases in our sample is different from that in the general populatio…

math.OC2018

An equivalence between critical points for rank constraints versus low-rank factorizations

Wooseok Ha, Haoyang Liu, Rina Foygel Barber

Two common approaches in low-rank optimization problems are either working directly with a rank constraint on the matrix variable, or optimizing over a low-rank factorization so th…

stat.ME2018

The conditional permutation test for independence while controlling for confounders

Thomas B. Berrett, Yi Wang, Rina Foygel Barber +1

We propose a general new method, the conditional permutation test, for testing the conditional independence of variables and given a potentially high-dimensional random vec…

stat.ML2018

Prediction Rule Reshaping

Matt Bonakdarpour, Sabyasachi Chatterjee, Rina Foygel Barber +1

Two methods are proposed for high-dimensional shape-constrained regression and classification. These methods reshape pre-trained prediction rules to satisfy shape constraints like…

physics.med-ph2018

Estimating the spectrum in computed tomography via Kullback-Leibler divergence constrained optimization

Wooseok Ha, Emil Y. Sidky, Rina Foygel Barber +2

We study the problem of spectrum estimation from transmission data of a known phantom. The goal is to reconstruct an x-ray spectrum that can accurately model the x-ray transmission…

stat.ME2018

Between hard and soft thresholding: optimal iterative thresholding algorithms

Haoyang Liu, Rina Foygel Barber

Iterative thresholding algorithms seek to optimize a differentiable objective function over a sparsity or rank constraint by alternating between gradient steps that reduce the obje…