Gaël Aglin

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it; #12,593 of 35,345 by trust here, #21,878 by citations
• Algorithms & Complexity — 11 citations into it; #350 of 516 by trust here, #310 by citations
• Computational Theory and Mathematics — 7 citations into it
• Information Systems — 7 citations into it; #4,360 of 8,771 by trust here, #5,501 by citations
• Statistical Learning Theory — 6 citations into it

Whom Gaël Aglin trusts overall

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

1. Siegfried Nijssen
2. J. Ross Quinlan
3. Niko Speybroeck
4. Florent Avellaneda
5. Sicco Verwer
6. Élisa Fromont
7. Christian Bessiere
8. Nina Narodytska
9. Rakesh Agrawal
10. Yingqian Zhang

Who trusts Gaël Aglin overall

1. Emir Demirovi'c
2. Peter James Stuckey
3. Emilio Carrizosa
4. Anna Lukina
5. Jinqiang Yu
6. Cynthia Rudin
7. Alexey Ignatiev
8. Emmanuel Hebrard
9. Yacine Izza
10. André Schidler

Papers from Gaël Aglin's perspective

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

1. Constructing Optimal Binary Decision Trees is NP-Complete
2. Learning Optimal Decision Trees with SAT
3. C4.5: Programs for Machine Learning
4. Induction of decision trees
5. Minimising Decision Tree Size as Combinatorial Optimisation
6. Fast Discovery of Association Rules
7. Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making
8. Classification and regression trees
9. Efficient Inference of Optimal Decision Trees
10. Optimal constraint-based decision tree induction from itemset lattices

Their papers

• PyDL8.5: a Library for Learning Optimal Decision Trees (2020) — 33 citations
• Learning Optimal Decision Trees Using Caching Branch-and-Bound Search (2020) — 139 citations