We have developed and implemented a case-based approach for introducing discrete event simulation to undergraduate and graduate manufacturing engineering students. Students learn ...
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
We propose a framework to learn statistical shape models for faces as piecewise linear models. Specifically, our methodology builds upon primitive active shape models(ASM) to hand...
Developing Web-based systems for agriculture and rural development requires the collaboration of experts from different scientific fields and backgrounds. Thus, it is crucial to ...
In this paper, we present a fast and scalable Bayesian model for improving weakly annotated data – which is typically generated by a (semi) automated information extraction (IE) ...