—We address the problem of estimating a random vector X from two sets of measurements Y and Z, such that the estimator is linear in Y . We show that the partially linear minimum ...
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Density biased sampling (DBS) has been proposed to address the limitations of Uniform sampling, by producing the desired probability distribution in the sample. The ease of produc...
A no-reference image metric based on the singular value decomposition of local image gradients is proposed in this paper. This metric provides a quantitative measure of true image...
Recently, there is an interest in using associations between web pages in providing users with pages relevant to what they are currently viewing. We believe that, to enable intell...