Recent years have seen a significant increase in our understanding of high-dimensional nearest neighbor search (NNS) for distances like the 1 and 2 norms. By contrast, our underst...
A Bayesian approach to analyze the modes of variation in a set of curves is suggested. It is based on a generative model thus allowing for noisy and sparse observations of curves....
We address the problem of minimum distance localization in environments that may contain self-similarities. A mobile robot is placed at an unknown location inside a ¢¤£ self-sim...
Computing frequent itemsets is one of the most prominent problems in data mining. We study the following related problem, called FREQSAT, in depth: given some itemset-interval pai...
Generative topographic mapping (GTM) is a statistical model to extract a hidden smooth manifold from data, like the self-organizing map (SOM). Although a deterministic search algo...