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Found 4 papers, 3 papers with code
Adults as Augmentations for Children in Facial Emotion Recognition with Contrastive Learning
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.
Model Learning with Personalized Interpretability Estimation (ML-PIE)
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.
Learning a Formula of Interpretability to Learn Interpretable Formulas
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.
Design, Validation, and Case Studies of 2D-VSR-Sim, an Optimization-friendly Simulator of 2-D Voxel-based Soft Robots
Voxel-based soft robots (VSRs) are aggregations of soft blocks whose design is amenable to optimization.
