Jeffrey Chan

Artificial Intelligence · with Bailey · 2020

A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 43 citations into it
• Algorithms & Complexity — 19 citations into it
• Information Systems — 19 citations into it
• Statistical Learning Theory — 15 citations into it
• Computational Theory and Mathematics — 13 citations into it
• Optimization & Training — 8 citations into it
• Mathematical Optimization — 5 citations into it

Whom Jeffrey Chan trusts overall

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

1. Siegfried Nijssen
2. Dimitris J. Bertsimas
3. Sicco Verwer
4. J. Ross Quinlan
5. Florent Avellaneda
6. Mohammed J. Zaki
7. Gaël Aglin
8. Yingqian Zhang
9. Usama M. Fayyad
10. Leo Breiman

Papers from Jeffrey Chan's perspective

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

1. Constructing Optimal Binary Decision Trees is NP-Complete
2. Classification and regression trees
3. C4.5: Programs for Machine Learning
4. Learning Optimal Decision Trees with SAT
5. Optimal classification trees
6. Minimising Decision Tree Size as Combinatorial Optimisation
7. Classification and regression trees
8. Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making
9. Learning Optimal Classification Trees Using a Binary Linear Program Formulation
10. Scikit-learn: Machine Learning in Python

Their papers

• MurTree: Optimal Decision Trees via Dynamic Programming and Search (2020) — 89 citations
• MurTree: Optimal Classification Trees via Dynamic Programming and Search (2020) — 19 citations