A. Poluzzi

Artificial Intelligence · 2020

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 — 13 citations into it
• Statistics and Probability — 11 citations into it
• Safety, Robustness & Interpretability — 10 citations into it
• Statistical Learning Theory — 5 citations into it

Whom A. Poluzzi trusts overall

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

1. Jerome H. Friedman
2. Marco Tulio Ribeiro
3. Alan Agresti

Papers from A. Poluzzi's perspective

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

1. Random Forests
2. Greedy function approximation: A gradient boosting machine.
3. Anchors: High-Precision Model-Agnostic Explanations
4. Association for Computational Linguistics " Why Should I Trust You? " Explaining the Predictions of Any Classifier
5. A Unified Approach to Interpreting Model Predictions
6. Ridge Regression: Biased Estimation for Nonorthogonal Problems
7. Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation
8. A Survey of Methods for Explaining Black Box Models
9. The elements of statistical learning: data mining, inference and prediction
10. Interpretable Machine Learning

Their papers

• Statistical stability indices for LIME: Obtaining reliable explanations for machine learning models (2020) — 219 citations