Utilizing spatial index structures on secondary memory for nearest neighbor search in high-dimensional data spaces has been the subject of much research. With the potential to host...
Christoph Brochhaus, Marc Wichterich, Thomas Seidl
In many modern application ranges high-dimensional feature vectors are used to model complex real-world objects. Often these objects reside on different local sites. In this paper,...
Hans-Peter Kriegel, Peter Kunath, Martin Pfeifle, ...
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
We address the problem of designing data structures that allow efficient search for approximate nearest neighbors. More specifically, given a database consisting of a set of vecto...
In this paper we present a clustering and indexing paradigm called Clindex for high-dimensional search spaces. The scheme is designed for approximate similarity searches, where on...
Chen Li, Edward Y. Chang, Hector Garcia-Molina, Gi...