Graphical models are fundamental tools for modeling images and other applications. In this paper, we propose the Logistic Random Field (LRF) model for representing a discrete-valu...
Marshall F. Tappen, Kegan G. G. Samuel, Craig V. D...
Graphical models are useful for capturing interdependencies of statistical variables in various fields. Estimating parameters describing sparse graphical models of stationary mul...
Traditional binary hypothesis testing relies on the precise knowledge of the probability density of an observed random vector conditioned on each hypothesis. However, for many app...
The singular value decomposition (SVD) is fundamental to many data modeling/mining algorithms, but SVD algorithms typically have quadratic complexity and require random access to ...
In today’s continuously changing markets newly developed products often do not meet the demands and expectations of customers. Research on this problem identified a large gap b...