M. Zambon

2004

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Whom M. Zambon trusts overall

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

1. Yoav Freund
2. Jerome H. Friedman
3. Rick L. Lawrence
4. Robert E. Schapire

Who trusts M. Zambon overall

1. Dominique Arrouays
2. Manuel P. Martin

Papers from M. Zambon's perspective

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

1. Experiments with a New Boosting Algorithm
2. Greedy function approximation: A gradient boosting machine.
3. Boosting the margin: A new explanation for the effectiveness of voting methods
4. Stochastic gradient boosting
5. An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants
6. A Short Introduction to Boosting
7. Popular Ensemble Methods: An Empirical Study
8. Rule-Based Classification Systems Using Classification and Regression Tree (CART) Analysis
9. An assessment of the effectiveness of decision tree methods for land cover classification
10. UCI Repository of machine learning databases

Their papers

• Classification of remotely sensed imagery using stochastic gradient boosting as a refinement of classification tree analysis (2004) — 332 citations