We present techniques for discovering and exploiting regularity in large curvilinear data sets. The data can be based on a single mesh or a mesh composed of multiple submeshes (al...
In this paper, we examine the problem of learning from noisecontaminated data in high-dimensional space. A new learning approach based on projections onto multi-dimensional ellips...
Abstract. We are designing new data mining techniques on gene expression data, more precisely inductive querying techniques that extract a priori interesting bi-sets, i.e., sets of...
e by placing terms in an abstract ‘information space’ based on their occurrences in text corpora, and then allowing a user to visualize local regions of this information space....
Procedural encoding of scattered and unstructured scalar datasets using Radial Basis Functions (RBF) is an active area of research with great potential for compactly representing ...
Manfred Weiler, Ralf P. Botchen, Simon Stegmaier, ...