Thoughit has been possible in the past to learn to predict DNAhydration patterns from crystallographic data, there is ambiguity in the choice of training data (both in terms of th...
Dawn M. Cohen, Casimir A. Kulikowski, Helen Berman
In this paper we investigate the role of user emotions in human-machine goal-oriented conversations. There has been a growing interest in predicting emotions from acted and non-act...
Many machine-learning algorithms learn rules of behavior from individual end users, such as taskoriented desktop organizers and handwriting recognizers. These rules form a “prog...
Todd Kulesza, Simone Stumpf, Margaret M. Burnett, ...
In this paper we propose a schema and framework for recording and managing attention metadata. This framework is intended to capture, manage, and re-use data about attention users...
This paper presents ABLO, a first-attempt at engineering a more active learning object based on agent technologies that allows more sophisticated kinds of learning object reuse tha...