1 citations · 1 across the 2 of their papers we have counts for
3 papers
s-LIME: Reconciling Locality and Fidelity in Linear Explanations
Romaric Gaudel, Luis Galárraga, Julien Delaunay +2
The benefit of locality is one of the major premises of LIME, one of the most prominent methods to explain black-box machine learning models. This emphasis relies on the postulate…
Making ML models fairer through explanations: the case of LimeOut
Guilherme Alves, Vaishnavi Bhargava, Miguel Couceiro +1
Algorithmic decisions are now being used on a daily basis, and based on Machine Learning (ML) processes that may be complex and biased. This raises several concerns given the criti…
LimeOut: An Ensemble Approach To Improve Process Fairness
Vaishnavi Bhargava, Miguel Couceiro, Amedeo Napoli
Artificial Intelligence and Machine Learning are becoming increasingly present in several aspects of human life, especially, those dealing with decision making. Many of these algor…