We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
Abundant content, data type and diverse members' interests naturally lead to preference heterogeneity within a multicast session requiring frequent communication within subgr...
The self-organising map (SOM) has been successfully employed as a nonparametric method for dimensionality reduction and data visualisation. However, for visualisation the SOM requ...
Abstract—Segmenting lesions is a vital step in many computerized mass-detection schemes for digital (or digitized) mammograms. We have developed two novel lesion segmentation tec...
This paper presents a solution for texture mapping unparameterized models. The quality of a texture on a model is often limited by the model's parameterization into a 2D text...
David (grue) DeBry, Jonathan Gibbs, Devorah DeLeon...