Active Learning (AL) is a selective sampling strategy which has been shown to be particularly cost-efficient by drastically reducing the amount of training data to be manually ann...
We present a computational framework designed to provide adaptive support aimed at triggering learning from problem-solving activities in the presence of worked-out examples. The k...
This work proposes concepts, designs, experiences and lessons learned from some studies of ad hoc learning supported by wireless and mobile technologies. The ad hoc learning activi...
Most work on Predictive Representations of State (PSRs) has focused on learning and planning in unstructured domains (for example, those represented by flat POMDPs). This paper e...
David Wingate, Vishal Soni, Britton Wolfe, Satinde...
This article proposes an active basis model and a shared pursuit algorithm for learning deformable templates from image patches of various object categories. In our generative mod...
Ying Nian Wu, Zhangzhang Si, Chuck Fleming, Song C...