This paper describes the result of our study on neural learning to solve the classification problems in which data is unbalanced and noisy. We conducted the study on three differen...
We propose a new model for the probabilistic estimation of continuous state variables from a sequence of observations, such as tracking the position of an object in video. This ma...
In this paper we discuss our initial experiences adapting OpenMP to enable it to serve as a programming model for high performance embedded systems. A high-level programming model...
Barbara M. Chapman, Lei Huang, Eric Biscondi, Eric...
Discriminative learning techniques for sequential data have proven to be more effective than generative models for named entity recognition, information extraction, and other task...
The Multimedia and Information Systems group at the Knowledge Media Institute of the Open University participated in the Expert Search and Document Search tasks of the Enterprise ...