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Influential features PCA for high dimensional clustering

scholarly article; Ann. Statist 2016 (with discussion/rejoinder)
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Influential features PCA for high dimensional clustering

Summary

Influential features PCA for high dimensional clustering is an academic journal article[1].

Key Facts

  • Influential features PCA for high dimensional clustering authored Jiashun Jin[2].
  • Influential features PCA for high dimensional clustering authored Wanjie Wang[3].
  • Influential features PCA for high dimensional clustering's instance of is recorded as academic journal article[4].
  • Influential features PCA for high dimensional clustering's page is recorded as 2323-2359[5].
  • Influential features PCA for high dimensional clustering's DOI is recorded as 10.1214/15-AOS1423[6].
  • Influential features PCA for high dimensional clustering's issue is recorded as 6[7].
  • Influential features PCA for high dimensional clustering's volume is recorded as 44[8].
  • Influential features PCA for high dimensional clustering's publication date is recorded as +2016-12-00T00:00:00Z[9].
  • Influential features PCA for high dimensional clustering's JSTOR article ID is recorded as 44245751[10].
  • Influential features PCA for high dimensional clustering's Mathematical Reviews ID is recorded as 3576543[11].
  • Influential features PCA for high dimensional clustering's zbMATH Open document ID is recorded as 1359.62249[12].
  • Influential features PCA for high dimensional clustering's main subject is recorded as cluster analysis[13].
  • Influential features PCA for high dimensional clustering's work available at URL is recorded as https://projecteuclid.org/journalArticle/Download?urlId=10.1214%2F15-AOS1423[14].
  • Influential features PCA for high dimensional clustering's number of pages is recorded as {'unit': '1', 'amount': '+37'}[15].
  • Influential features PCA for high dimensional clustering's published in is recorded as Annals of Statistics[16].
  • Influential features PCA for high dimensional clustering's title is recorded as Influential features PCA for high dimensional clustering[17].
  • Influential features PCA for high dimensional clustering's cites work is recorded as Higher criticism for detecting sparse heterogeneous mixtures[18].
  • Influential features PCA for high dimensional clustering's cites work is recorded as Higher criticism thresholding: Optimal feature selection when useful features are rare and weak[19].
  • Influential features PCA for high dimensional clustering's cites work is recorded as The Elements of Statistical Learning[20].
  • Influential features PCA for high dimensional clustering's cites work is recorded as Boundary Crossing Probabilities for Locally Poisson Processes[21].

Body

Designation and Status

Influential features PCA for high dimensional clustering's instance of is recorded as academic journal article[4].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [4] ↑ . wikidata.org.
  2. [2] ↑ . wikidata.org.
  3. [3] ↑ . wikidata.org.
  4. [5] ↑ . wikidata.org.
  5. [6] ↑ . wikidata.org.
  6. [7] ↑ . wikidata.org.
  7. [8] ↑ . wikidata.org.
  8. [9] ↑ . wikidata.org.
  9. [10] ↑ . wikidata.org.
  10. [11] ↑ . wikidata.org.
  11. [12] ↑ . wikidata.org.
  12. [13] ↑ . wikidata.org.
  13. [14] ↑ . wikidata.org.
  14. [15] ↑ . wikidata.org.
  15. [16] ↑ . wikidata.org.
  16. [17] ↑ . wikidata.org.
  17. [18] ↑ . wikidata.org.
  18. [19] ↑ . wikidata.org.
  19. [20] ↑ . wikidata.org.
  20. [21] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Influential features PCA for high dimensional clustering. Retrieved May 3, 2026, from https://4ort.xyz/entity/influential-features-pca-for-high-dimensional-clustering
MLA “Influential features PCA for high dimensional clustering.” 4ort.xyz Knowledge Graph, 4ort.xyz, 3 May. 2026, https://4ort.xyz/entity/influential-features-pca-for-high-dimensional-clustering.
BibTeX @misc{4ortxyz_influential-features-pca-for-high-dimensional-clustering_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Influential features PCA for high dimensional clustering}}, year = {2026}, url = {https://4ort.xyz/entity/influential-features-pca-for-high-dimensional-clustering}, note = {Accessed: 2026-05-03}}
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