Eric Rice

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 7 citations into it
• Safety, Robustness & Interpretability — 5 citations into it

Whom Eric Rice trusts overall

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

1. Yin Lou

Papers from Eric Rice's perspective

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

1. Accurate intelligible models with pairwise interactions
2. Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model
3. Intelligible models for classification and regression
4. Interpretable Decision Sets: A Joint Framework for Description and Prediction
5. Best Subset Selection via a Modern Optimization Lens
6. Interpretable Deep Models for ICU Outcome Prediction
7. MediBoost: a Patient Stratification Tool for Interpretable Decision Making in the Era of Precision Medicine
8. The Discrete Dantzig Selector: Estimating Sparse Linear Models via Mixed Integer Linear Optimization
9. A Bayesian Framework for Learning Rule Sets for Interpretable Classification
10. Regression Shrinkage and Selection via the Lasso

Their papers

• Designing Fair, Efficient, and Interpretable Policies for Prioritizing Homeless Youth for Housing Resources (2018) — 65 citations