This paper presents a search algorithm for finding functions that are highly correlated with an arbitrary set of data. The functions found by the search can be used to approximate...
Abstract. We present The Cruncher, a simple representation framework and algorithm based on minimum description length for automatically forming an ontology of concepts from attrib...
We explore generic mechanisms to introduce structural hints into the method of Unsupervised Kernel Regression (UKR) in order to learn representations of data sequences in a semi-su...
Jan Steffen, Stefan Klanke, Sethu Vijayakumar, Hel...
We have analyzed manufacturing data from several different semiconductor manufacturing plants, using decision tree induction software called Q-YIELD. The software generates rules ...
This work is designed to contribute to a deeper understanding of the recently proposed Merging SOM (MSOM). Its context model aims at the representation of sequences, an important s...