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researcher

R. Barber

63 papers hereh-index 335.6k citations91 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author20
  • middle author20
  • last author22

Across the 63 of 63 papers where every author was matched, so the position is known.

fields
  • stat.ME32
  • math.ST20
  • math.OC5
  • physics.med-ph3
  • stat.ML2
  • cs.LG1
same name
  • R. Barber — 14 papers, h 23
  • R. Barber — 2 papers, h 16
  • R. Barber — 1 paper, h 27
  • R. Barber — 1 paper, h 0

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20142026
most citedControlling the false discovery rate via knockoffs

575 citations · 929 across the 52 of their papers we have counts for

collaborators
Showing 2022 · stat.MEShow all

4 papers · 2 filters

stat.ME2022

Conformalized survival analysis with adaptive cutoffs

Yu Gui, Rohan Hore, Zhimei Ren +1

This paper introduces an assumption-lean method that constructs valid and efficient lower predictive bounds (LPBs) for survival times with censored data. We build on recent work by…

stat.ME2022★ 3 cited

Derandomized knockoffs: leveraging e-values for false discovery rate control

Zhimei Ren, Rina Foygel Barber

Model-X knockoffs is a flexible wrapper method for high-dimensional regression algorithms, which provides guaranteed control of the false discovery rate (FDR). Due to the randomnes…

stat.ME2022★ 1 cited

Permutation tests using arbitrary permutation distributions

Aaditya Ramdas, Rina Foygel Barber, Emmanuel J. Candes +1

Permutation tests date back nearly a century to Fisher's randomized experiments, and remain an immensely popular statistical tool, used for testing hypotheses of independence betwe…

stat.ME2022★ 7 cited

Conformal prediction beyond exchangeability

Rina Foygel Barber, Emmanuel J. Candes, Aaditya Ramdas +1

Conformal prediction is a popular, modern technique for providing valid predictive inference for arbitrary machine learning models. Its validity relies on the assumptions of exchan…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.