Weakly Supervised Multi-task Learning for Concept-based Explainability
@article{Belem2021WeaklySM, title={Weakly Supervised Multi-task Learning for Concept-based Explainability}, author={Catarina Bel'em and Vladimir Balayan and Pedro Saleiro and P. Bizarro}, journal={ArXiv}, year={2021}, volume={abs/2104.12459} }
In ML-aided decision-making tasks, such as fraud detection or medical diagnosis, the human-in-the-loop, usually a domain-expert without technical ML knowledge, prefers high-level concept-based explanations instead of low-level explanations based on model features. To obtain faithful concept-based explanations, we leverage multi-task learning to train a neural network that jointly learns to predict a decision task based on the predictions of a precedent explainability task (i.e., multi-label…
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