In this work we focus on machine teaching [Zhu2018], which is the inverse problem of machine learning. Machine teaching studies the interaction between a teacher and a learner. Given a learning model and a target, the teacher aims to find an optimal set of training examples for the learner. In such a setting, the teacher selects a set of training examples based on previous learner performances. Machine teaching has been developed and applied in several contexts including education and adversarial settings (e.g., attacks).
AgeNts Distribues, Robotique, Recherche Opérationnelle, Interaction, DEcision