Ryan McNellis

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it
• Statistics and Probability — 15 citations into it
• Statistical Learning Theory — 9 citations into it
• Management Science and Operations Research — 7 citations into it
• Algorithms & Complexity — 5 citations into it
• Information Systems — 5 citations into it

Whom Ryan McNellis trusts overall

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

1. Dimitris J. Bertsimas
2. Adam N. Elmachtoub
3. Nathan Kallus
4. Niko Speybroeck
5. Sina Aghaei
6. Wei-Yin Loh
7. Leo Breiman
8. R. Heale
9. Jack Dunn

Papers from Ryan McNellis's perspective

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

1. Optimal classification trees
2. Classification and regression trees
3. Points of Significance: Classification and regression trees
4. Analytics for an Online Retailer: Demand Forecasting and Price Optimization (Manufacturing & Service Operations Management)
5. European Union Regulations on Algorithmic Decision-Making and a "Right to Explanation"
6. Logistic Model Trees
7. Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making
8. Model-Based Recursive Partitioning
9. Optimization of Tree Ensembles
10. Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization (AAAI Conference on Artificial Intelligence)

Their papers

• Market Segmentation Trees (2019) — 29 citations
• Decision Trees for Decision-Making under the Predict-then-Optimize Framework (2020) — 147 citations