Abstract. When faced with the task of building accurate classifiers, active learning is often a beneficial tool for minimizing the requisite costs of human annotation. Traditional ...
Lessons learned systems (LLS) are systems that support a lessons learned process (LLP) to collect, verify, store, disseminate, and reuse organizational lessons. In this paper we e...
Property testing deals with tasks where the goal is to distinguish between the case that an object (e.g., function or graph) has a prespecified property (e.g., the function is li...
Active learning may hold the key for solving the data scarcity problem in supervised learning, i.e., the lack of labeled data. Indeed, labeling data is a costly process, yet an ac...
Learning from end-users is essential to participatory design. In order to learn from end-users we need to find end-users to collaborate with. However, finding end-users can be the...
Rachel K. E. Bellamy, Tracee Vetting Wolf, Rhonda ...