Human-AI teaming refers to systems in which humans and artificial intelligence (AI) agents
collaborate to provide significant mission performance improvements over that which …

In this article, we propose a communicative learning (CL) formalism that unifies existing
machine learning paradigms, such as passive learning, active learning, algorithmic …

Teaching unbiased decision-making is crucial for addressing biased decision-making in
daily life. Although both raising awareness of personal biases and providing guidance on …

State-of-the-art deep-learning systems use decision rules that are challenging for humans to
model. Explainable AI (XAI) attempts to improve human understanding but rarely accounts …

We study the problem of computer-assisted teaching with explanations. Conventional
approaches for machine teaching typically only provide feedback at the instance level eg …

In this paper, we make an important step towards the black-box machine teaching by
considering the cross-space machine teaching, where the teacher and the learner use …

In real-world applications of education, an effective teacher adaptively chooses the next
example to teach based on the learner's current state. However, most existing work in …

The problem of machine teaching is considered. A new formulation is proposed under the
assumption of an optimal student, where optimality is defined in the usual machine learning …

The emergence of the Internet-of-Things (IoT) sheds light on applying the machine teaching
(MT) algorithms for online personalized education on home devices. This direction becomes …

We consider the problem of iterative machine teaching, where a teacher sequentially
provides examples based on the status of a learner under a discrete input space (ie, a pool …