Evidence map›Paper›PMID 31598016›Full record

ArticleAnnals of statistics2019

SPECTRAL METHOD AND REGULARIZED MLE ARE BOTH OPTIMAL FOR TOP-

Yuxin Chen, Jianqing Fan, Cong Ma, Kaizheng Wang

Abstract read
In one paragraph

Article in Annals of statistics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Spectral State Compression of Markov Processes.IEEE transactions on information theory · 2020
    Article
  8. NOISY MATRIX COMPLETION: UNDERSTANDING STATISTICAL GUARANTEES FOR CONVEX RELAXATION VIA NONCONVEX OPTIMIZATION.SIAM journal on optimization : a publication of the Society for Industrial and Applied Mathematics · 2020
    Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yuxin ChenDepartment of Electrical Engineering, Princeton University Princeton, New Jersey 08544, yuxin.chen@princeton.edu.
Jianqing FanSchool of Data Science, Fudan University, Shanghai, China, and, Department of Operations Research &, Financial Engineering, Princeton, University, Princeton New Jersey 08544, jqfan@princeton.edu.
Cong MaDepartment of Operations Research &, Financial Engineering, Princeton University, Princeton, New Jersey 08544, congm@princeton.edu.
Kaizheng WangDepartment of Operations Research &, Financial Engineering, Princeton University, Princeton, New Jersey 08544, kaizheng@princeton.edu.

Funding

Statistical Methods for Ultrahigh-dimensional Biomedical DataR01GM072611 · NIGMS · PRINCETON UNIVERSITY · PI CATTANEO, MATIAS DAMIAN · 2006 to 2021
$4.2M
NIGMS NIH HHS R01 GM072611
6 · The paper itself

Abstract

This paper is concerned with the problem of top-

Indexed as

entrywise perturbationleave-one-out analysispairwise comparisonsregularized MLEreversible Markov chainsspectral methodtop-K ranking

Identifiers

PMID31598016
PMCPMC6785035

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.