We present a new approach to semi-supervised anomaly detection. Given a set of training examples believed to come from the same distribution or class, the task is to learn a model ...
It is becoming increasingly common to construct databases from information automatically culled from many heterogeneous sources. For example, a research publication database can b...
Aron Culotta, Michael L. Wick, Robert Hall, Matthe...
Abstract. This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an ...
Abstract. Decision making is an important aspect of meetings in organisational settings, and archives of meeting recordings constitute a valuable source of information about the de...
If the dataset available to machine learning results from cluster sampling (e.g. patients from a sample of hospital wards), the usual cross-validation error rate estimate can lead...