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Yuting Wei

University of Pennsylvania

12 papers hereh-index 252.2k citations73 works total

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

author position
  • first author2
  • middle author6
  • last author4

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • math.ST4
  • stat.ML4
  • cs.LG2
  • stat.ME2
affiliations
  • University of Pennsylvania
Homepage
same name
  • Yuting Wei — 14 papers, h 11
  • Yuting Wei — 6 papers, h 6
  • Yuting Wei — 5 papers, h 7
  • Yuting Wei — 2 papers
  • Yuting Wei — 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
20182023
most citedDerandomizing Knockoffs

6 citations · 27 across the 8 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

stat.ME2020★ 6 cited

Derandomizing Knockoffs

Zhimei Ren, Yuting Wei, Emmanuel Candès

Model-X knockoffs is a general procedure that can leverage any feature importance measure to produce a variable selection algorithm, which discovers true effects while rigorously c…

stat.ML2020★ 4 cited

Debiasing Evaluations That are Biased by Evaluations

Jingyan Wang, Ivan Stelmakh, Yuting Wei +1

It is common to evaluate a set of items by soliciting people to rate them. For example, universities ask students to rate the teaching quality of their instructors, and conference…

stat.ME2020★ 3 cited

Randomized tests for high-dimensional regression: A more efficient and powerful solution

Yue Li, Ilmun Kim, Yuting Wei

We investigate the problem of testing the global null in the high-dimensional regression models when the feature dimension p grows proportionally to the number of observations $n…

stat.ML2020★ 6 cited

Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification

Chen Dan, Yuting Wei, Pradeep Ravikumar

Adversarial robustness has become a fundamental requirement in modern machine learning applications. Yet, there has been surprisingly little statistical understanding so far. In th…

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