Human-in-the-loop online multi-agent approach to increase trustworthiness in ML models through trust scores and data augmentation
Published in IEEE Computer Software and Applications Conference (COMPSAC), 2022
Recommended citation: Bravo-Rocca, G., et al. (2022). "Human-in-the-loop online multi-agent approach to increase trustworthiness in ML models through trust scores and data augmentation." IEEE COMPSAC 2022. https://doi.org/10.1109/COMPSAC54236.2022.00014
A human-in-the-loop online multi-agent approach that increases trustworthiness in ML models through trust scores and data augmentation. This work laid the foundations of the trustworthy AI and agent-based monitoring research line at Barcelona Supercomputing Center & Lenovo.
Recommended citation: Bravo-Rocca, G., et al. (2022). “Human-in-the-loop online multi-agent approach to increase trustworthiness in ML models through trust scores and data augmentation.” IEEE COMPSAC 2022.