In this paper, we propose the Kernel Laplacian Eigenmaps for nonlinear dimensionality reduction. This method can be extended to any structured input beyond the usual vectorial data...
Even though geo data are getting more and more widely available nowadays, they often do not meet the requirements of location-based services concerning structure, content and forma...
In this paper, we present the results of an investigation into methodologies and technical solutions for exposing the structured metadata contained within digital qualitative data...
As relational databases proliferate and become increasingly complex, both in their internal structure and in their interactions with other databases and applications, there is a g...
We consider the problem of classification in nonadaptive dimensionality reduction. Specifically, we bound the increase in classification error of Fisher’s Linear Discriminant...