Modeling human behavior requires vast quantities of accurately labeled training data, but for ubiquitous people-aware applications such data is rarely attainable. Even researchers...
Daniel Peebles, Hong Lu, Nicholas D. Lane, Tanzeem...
We discuss factors that affect human agreement on a semantic labeling task in the art history domain, based on the results of four experiments where we varied the number of labels...
Rebecca J. Passonneau, Thomas Lippincott, Tae Yano...
Many data mining applications can benefit from adapting existing classifiers to new data with shifted distributions. In this paper, we present Adaptive Support Vector Machine (Ada...
Most approaches to classifying media content assume a fixed, closed vocabulary of labels. In contrast, we advocate machine learning approaches which take advantage of the millions...
A significant portion of the world's text is tagged by readers on social bookmarking websites. Credit attribution is an inherent problem in these corpora because most pages h...
Daniel Ramage, David Hall, Ramesh Nallapati, Chris...