Representing lexicons and sentences with the subsymbolic approach (using techniques such as Self Organizing Map (SOM) or Artificial Neural Network (ANN)) is a relatively new but i...
Abstract. In this paper we present a coarse-grained parallel algorithm, CONQUEST, for constructing boundederror summaries of high-dimensional binary attributed data in a distribute...
A novel algorithm called Average Neighborhood Margin Maximization (ANMM) is proposed for supervised linear feature extraction. For each data point, ANMM aims at pulling the neighb...
The detection of correlations between different features in a set of feature vectors is a very important data mining task because correlation indicates a dependency between the fe...
We propose an unconventional but highly effective approach
to robust fitting of multiple structures by using statistical
learning concepts. We design a novel Mercer kernel
for t...