The creation of huge databases coming from both restoration of existing analogue archives and new content is demanding fast and more and more reliable tools for content analysis a...
We consider the problem of classification when multiple observations of a pattern are available, possibly under different transformations. We view this problem as a special case o...
Design patterns have been enthusiastically embraced in the software engineering community as well as in the web community since they capture knowledge about how and when to apply a...
We present a new approach, called local discriminant embedding (LDE), to manifold learning and pattern classification. In our framework, the neighbor and class relations of data a...
The paper presents a framework for semi-supervised nonlinear embedding methods useful for exploratory analysis and visualization of spatio-temporal network data. The method provid...