no code implementations • 10 Feb 2022 • Marco Virgolin, Andrea De Lorenzo, Tanja Alderliesten, Peter A. N. Bosman
Our results indicate that adult data can be considered to be a meaningful augmentation of pediatric data for the recognition of emotional facial expression in children, and open up the possibility for other applications of contrastive learning to improve pediatric care by complementing data of children with that of adults.
1 code implementation • 13 Apr 2021 • Marco Virgolin, Andrea De Lorenzo, Francesca Randone, Eric Medvet, Mattias Wahde
The latter is estimated by a neural network that is trained concurrently to the evolution using the feedback of the user, which is collected using uncertainty-based active learning.
3 code implementations • 23 Apr 2020 • Marco Virgolin, Andrea De Lorenzo, Eric Medvet, Francesca Randone
We show that it is instead possible to take a meta-learning approach: an ML model of non-trivial Proxies of Human Interpretability (PHIs) can be learned from human feedback, then this model can be incorporated within an ML training process to directly optimize for interpretability.
2 code implementations • 23 Jan 2020 • Eric Medvet, Alberto Bartoli, Andrea De Lorenzo, Stefano Seriani
Voxel-based soft robots (VSRs) are aggregations of soft blocks whose design is amenable to optimization.