The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
In a constraint-drivenlayout synthesisenvironment,parasitic constraints are generated and implemented in each phase of the design process to meet a given set of performance specif...
Edoardo Charbon, Paolo Miliozzi, Enrico Malavasi, ...
In this paper we describe preliminary work that examines whether statistical properties of the structure of websites can be an informative measure of their quality. We aim to deve...
Vaclav Petricek, Tobias Escher, Ingemar J. Cox, He...
We present a novel matching and similarity evaluation method for planar geometric shapes represented by sets of polygonal curves. Given two shapes, the matching algorithm randomly...
The purpose of this paper is to characterize a constituent boundary parsing algorithm, using an information-theoretic measure called generalized mutual information, which serves a...