Explaining Predictions from Tree-based Boosting Ensembles

Answer Interaction in Non-factoid Question Answering Systems

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Model-Agnostic Interpretability of Machine Learning

Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin. 2016a · 2016

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Do news consumers want explanations for personalized news rankings?. In FATREC Workshop on Responsible Recommendation

Maartje ter Hoeve, Mathieu Heruer, Daan Odijk, Anne Schuth, Martijn Spitters, and Maarten de Rijke. 2017 · 2017

Cited alongside, same era.

Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking

Original

Gabriele Tolomei, Fabrizio Silvestri, Andrew Haines, and Mounia Lalmas. 2017 · 2017

Cited alongside, same era.

Explainable Machine Learning Challenge

FICO. [n. d.]

Cited in the paper.

Why should I trust you?: Explaining the predictions of any classifier. In KDD

Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin. 2016b

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On the Robustness of Interpretability Methods

Original

David Alvarez-Melis and Tommi S. Jaakkola. 2018 · 2018

Later among the works it cites.

A survey of methods for explaining black box models

Original

Riccardo Guidotti, Anna Monreale, Franco Turini, Dino Pedreschi, and Fosca Giannotti. 2018 · 2018

Later among the works it cites.

Explanation in artificial intelligence: Insights from the social sciences

Tim Miller. 2019 · 2019

Closest in time.