: We present the use of mapping functions to automatically generate levels of detail with known error bounds for polygonal models. We develop a piece-wise linear mapping function f...
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classifier, is formulated as a concave minimiza...
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
We are interested in the design of automated procedures for analyzing the (in)security of cryptographic protocols in the Dolev-Yao model for a bounded number of sessions when we t...
The problem of discriminating between two nite point sets in n-dimensional feature space by a separating plane that utilizes as few of the features as possible, is formulated as a...
Paul S. Bradley, Olvi L. Mangasarian, W. Nick Stre...