We study the problem of teaching multiple learners simultaneously in the nonparametric iterative teaching setting, where the teacher iteratively provides examples to the learner for accelerating the acquisition of a target concept. This problem is motivated by the gap between current single-learner teaching setting and the real-world scenario of human instruction where a teacher typically imparts knowledge to multiple students. Under the new problem formulation, we introduce a novel framework -- Multi-learner Nonparametric Teaching (MINT). In MINT, the teacher aims to instruct multiple learners, with each learner focusing on learning a scalar-valued target model. To achieve this, we frame the problem as teaching a vector-valued target model and extend the target model space from a scalar-valued reproducing kernel Hilbert space used in single-learner scenarios to a vector-valued space. Furthermore, we demonstrate that MINT offers significant teaching speed-up over repeated single-learner teaching, particularly when the multiple learners can communicate with each other. Lastly, we conduct extensive experiments to validate the practicality and efficiency of MINT.

翻译：我们研究了在非参数迭代教学场景中同时教授多个学习者的问题，其中教师通过迭代提供示例来加速学习者对目标概念的获取。该问题的动机源于当前单学习者教学设置与现实人类教学场景之间的差距——在实际教学中，教师通常同时向多名学生传授知识。基于这一新问题框架，我们提出了一种创新方法——多学习者非参数教学（MINT）。在MINT中，教师旨在指导多个学习者，每个学习者的学习目标是一个标量值的目标模型。为实现这一目标，我们将该问题形式化为教授一个向量值目标模型，并将目标模型空间从单学习者场景中使用的标量值再生核希尔伯特空间扩展到向量值空间。此外，我们证明MINT相比重复的单学习者教学能显著加速教学过程，尤其是在多个学习者可以相互通信的情况下。最后，我们通过大量实验验证了MINT的实用性和高效性。