Jacqueline J. Meulman

Artificial Intelligence · 2000–2005

A researcher in the Science corpus: 4 papers; trusts 2 researchers and is trusted by 31 researchers here, as inferred from the citation graph.

Subfields

Whom Jacqueline J. Meulman trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Jerome H. Friedman
  2. John C. Gower
  3. R. Fisher
  4. Joseph B. Kruskal
  5. Leo Breiman

Who trusts Jacqueline J. Meulman overall

  1. Jane Elith
  2. Daniela M. Witten
  3. Wei Pan
  4. Sara Dolnicar
  5. Simon C. Barry
  6. Adrian E. Raftery
  7. Marco Sandri
  8. J. Leathwick
  9. Daniel Müller
  10. Cathy Maugis

Papers from Jacqueline J. Meulman's perspective

Ordered by how strongly the researchers Jacqueline J. Meulman trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Algorithms for Clustering Data
  2. Greedy function approximation: A gradient boosting machine.
  3. Mixture models : inference and applications to clustering
  4. THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS
  5. Experiments with a New Boosting Algorithm
  6. Plaid models for gene expression data
  7. On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality
  8. A General Coefficient of Similarity and Some of Its Properties
  9. The approximation of one matrix by another of lower rank
  10. Estimating Optimal Transformations for Multiple Regression and Correlation.

Their papers