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researcher

M. Bogdan

33 papers hereh-index 232.4k citations96 works total

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

author position
  • first author5
  • middle author14
  • last author13

Across the 32 of 33 papers where every author was matched, so the position is known.

fields
  • math.ST9
  • stat.ME9
  • astro-ph.HE4
  • stat.ML4
  • astro-ph.CO3
  • astro-ph.IM1
same name
  • M. Bogdan — 16 papers, h 16
  • M. Bogdan — 8 papers, h 5
  • M. Bogdan — 3 papers, h 9
  • M. Bogdan — 3 papers, h 3
  • M. Bogdan — 1 paper, h 2
  • M. Bogdan — 1 paper, h 1

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
20082023
most citedSLOPE - Adaptive variable selection via convex optimization

291 citations · 936 across the 29 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

stat.CO2020★ 3 cited

VARCLUST: clustering variables using dimensionality reduction

Piotr Sobczyk, Stanislaw Wilczynski, Malgorzata Bogdan +5

VARCLUST algorithm is proposed for clustering variables under the assumption that variables in a given cluster are linear combinations of a small number of hidden latent variables,…

stat.ME2020

Identifying important predictors in large data bases -- multiple testing and model selection

Malgorzata Bogdan, Florian Frommlet

This is a chapter of the forthcoming Handbook of Multiple Testing. We consider a variety of model selection strategies in a high-dimensional setting, where the number of potential…

math.ST2020★ 2 cited

A Power Analysis for Model-X Knockoffs with ℓp​-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…

stat.ML2020★ 3 cited

The Strong Screening Rule for SLOPE

Johan Larsson, Małgorzata Bogdan, Jonas Wallin

Extracting relevant features from data sets where the number of observations (n) is much smaller then the number of predictors (p) is a major challenge in modern statistics. So…

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