B. Roe

Statistical Learning Theory · with Mills · 2004–2020

A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Statistical Learning Theory — 6 citations into it

Whom B. Roe trusts overall

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

1. Jerome H. Friedman
2. Yoav Freund
3. Robert E. Schapire
4. Leo Breiman

Who trusts B. Roe overall

1. Anna Veronika Dorogush
2. Polina Kirichenko
3. Liudmila Ostroumova
4. Giuseppe Carleo
5. Pavel Izmailov
6. Vasily Ershov
7. Andrey Gulin

Papers from B. Roe's perspective

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

1. Greedy function approximation: A gradient boosting machine.
2. Classification and regression trees
3. Experiments with a New Boosting Algorithm
4. The Boosting Approach to Machine Learning An Overview
5. A Short Introduction to Boosting
6. The MiniBooNE Collaboration
7. Game theory, on-line prediction and boosting
8. Bias, Variance , And Arcing Classifiers
9. The Strength of Weak Learnability
10. A theory of the learnable

Their papers

• Updated MiniBooNE neutrino oscillation results with increased data and new background studies (2020) — 152 citations
• The MiniBooNE Collaboration (2008) — 801 citations
• Boosted decision trees as an alternative to artificial neural networks for particle identification (2004) — 600 citations