One-class classification naturally only provides one-class of exemplars, the target class, from which to construct the classification model. The one-class approach is constructed...
Researchers that make tutoring systems would like to know which pieces of educational content are most effective at promoting learning among their students. Randomized controlled e...
This paper addresses the challenging problem of learning from multiple annotators whose labeling accuracy (reliability) differs and varies over time. We propose a framework based ...
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
We present further developments in our work on using data from real users to build a probabilistic model of user affect based on Dynamic Bayesian Networks (DBNs) and designed to de...