Many factorization models like matrix or tensor factorization have been proposed for the important application of recommender systems. The success of such factorization models dep...
Copulas have attracted much attention in spatial statistics over the past few years. They are used as a flexible alternative to traditional methods for nonGaussian spatial modelin...
We propose a framework for large scale learning and annotation of structured models. The system interleaves interactive labeling (where the current model is used to semiautomate t...
In the current paper, we outline several approaches to determine the value of information system (IS) flexibility, defined as the extent to which an IS can be modified and upgrade...
—A method to quantify the probabilistic controller taskload inherent to maintaining aircraft adherence to 4-D trajectories within flow corridors is presented. Taskload is here d...
Vlad Popescu, John-Paul Clarke, Karen M. Feigh, Er...
Discriminative mapping transforms (DMTs) is an approach to robustly adding discriminative training to unsupervised linear adaptation transforms. In unsupervised adaptation DMTs ar...
Modeling data by multiple low-dimensional planes is an important problem in many applications such as computer vision and pattern recognition. In the most general setting where on...
This paper describes a spatial model for healthcare workers' location in a large hospital facility. Such models have many applications in healthcare, such as supporting timea...
Donald Ephraim Curtis, Christopher S. Hlady, Srira...
A model for statistical ranking is a family of probability distributions whose states are orderings of a xed nite set of items. We represent the orderings as maximal chains in a ...
In our previous work, a precision constrained Gaussian model (PCGM) was proposed for character modeling to design compact recognizers of handwritten Chinese characters. A maximum ...