We present a novel family of data-driven linear transformations, aimed at visualizing multivariate data in a low-dimensional space in a way that optimally preserves the structure ...
As sensor networks increase in size and number, efficient techniques are required to process the very large data sets that they generate. Frequently, sensor networks monitor object...
In this paper, we consider energy-efficient gathering of correlated data in sensor networks. We focus on single-input coding strategies in order to aggregate correlated data. For ...
In this paper we propose a weakly supervised learning algorithm for appearance models based on the minimum description length (MDL) principle. From a set of training images or volu...
Georg Langs, Rene Donner, Philipp Peloschek, Horst...
The similarity join has become an important database primitive to support similarity search and data mining. A similarity join combines two sets of complex objects such that the r...