In this paper we try to organize machine teaching as a coherent set of ideas. Each idea is
presented as varying along a dimension. The collection of dimensions then form the …

In the contemporary exam-driven domain of education, each time a new technology
transpires, societies want to know how it can be used to make kids get superior grades, how …

I draw the reader's attention to machine teaching, the problem of finding an optimal training
set given a machine learning algorithm and a target model. In addition to generating …

The overarching goal of this work is to efficiently enable end-users to correctly anticipate a
robot's behavior in novel situations. And since a robot's behavior is often a direct result of its …

How to propagate label information from labeled examples to unlabeled examples over a
graph has been intensively studied for a long time. Existing graph-based propagation …

We study the empirical strategies that humans follow as they teach a target concept with a
simple 1D threshold to a robot. Previous studies of computational teaching, particularly the …

How should we present training examples to learners to teach them classification rules?
This is a natural problem when training workers for crowdsourcing labeling tasks, and is also …

What if there is a teacher who knows the learning goal and wants to design good training
data for a machine learner? We propose an optimal teaching framework aimed at learners …

One widely-studied model of teaching calls for a teacher to provide the minimal set of
labeled examples that uniquely specifies a target concept. The assumption is that the …

Compared to machines, humans are extremely good at classifying images into categories,
especially when they possess prior knowledge of the categories at hand. If this prior …