Abstract. We define a novel, basic, unsupervised learning problem learning the the lowest density homogeneous hyperplane separator of an unknown probability distribution. This task...
In flow-based mix networks, flow correlation attacks have been proposed earlier and have been shown empirically to seriously degrade mix-based anonymous communication systems. In ...
We show how to exploit the 32/64 bit architecture of modern computers to accelerate some of the algorithms used in satisfiability solving by modifying assignments to variables in ...
This paper presents a method for vectorizing the graphical parts of paper-based line drawings. The method consists of separating the input binary image into layers of homogeneous t...
We develop a statistical model to describe the spatially varying behavior of local neighborhoods of coefficients in a multiscale image representation. Neighborhoods are modeled as ...