Abstract. When seeking for small clusters it is very intricate to distinguish between incidental agglomeration of noisy points and true local patterns. We present the PAMALOC algor...
New applications of data mining, such as in biology, bioinformatics, or sociology, are faced with large datasets structured as graphs. We present an efficient algorithm for minin...
Projection pursuit was originally introduced to identify structures in multivariate data clouds (Huber, 1985). The idea of projecting data to a lowdimensional subspace can also be ...
Peter Filzmoser, Sven Serneels, Christophe Croux, ...
Dimensionality reduction is among the keys in mining highdimensional data. This paper studies semi-supervised dimensionality reduction. In this setting, besides abundant unlabeled...
We investigate the design of algorithms resilient to memory faults, i.e., algorithms that, despite the corruption of some memory values during their execution, are able to produce...