Scott L. Powell

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 Scott L. Powell 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
5. Eric Bauer
6. Richard Maclin

Who trusts Scott L. Powell overall

1. Dominique Arrouays
2. Manuel P. Martin

Papers from Scott L. Powell's perspective

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

1. Experiments with a New Boosting Algorithm
2. Boosting the margin: A new explanation for the effectiveness of voting methods
3. Greedy function approximation: A gradient boosting machine.
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