David A. Elizondo

Statistical Learning Theory · 2006–2008

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Statistical Learning Theory — 9 citations into it; #564 of 1,038 by trust here, #1,018 by citations
• Artificial Intelligence — 8 citations into it; #12,587 of 35,345 by trust here, #19,439 by citations
• Optimization & Training — 7 citations into it

Whom David A. Elizondo trusts overall

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

1. Chih-Wei Hsu
2. Chih-Jen Lin
3. Christopher K. I. Williams
4. Dustin Boswell
5. R. Fisher
6. J. Ross Quinlan
7. Tin Kam Ho
8. Yoav Freund
9. Leo Breiman
10. Jerome H. Friedman

Who trusts David A. Elizondo overall

1. Johanni Brea
2. Olivier J. H'enaff
3. Walter Senn
4. A. Srinivas
5. Jean-Pascal Pfister
6. Jeffrey De Fauw

Papers from David A. Elizondo's perspective

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

1. Bagging Predictors
2. Programs for Machine Learning
3. Neural Networks for Pattern Recognition
4. Fast Training of Support Vector Machines using Sequential Minimal Optimization
5. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
6. A decision-theoretic generalization of on-line learning and an application to boosting
7. Special Invited Paper-Additive logistic regression: A statistical view of boosting
8. THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS
9. Experiments with a New Boosting Algorithm
10. Boosting the margin: A new explanation for the effectiveness of voting methods

Their papers

• The linear separability problem: some testing methods (2006) — 125 citations
• Bankruptcy forecasting: An empirical comparison of AdaBoost and neural networks (2008) — 298 citations