Abstract. Many applications of machine learning involve sparse highdimensional data, where the number of input features is (much) larger than the number of data samples, d n. Predi...
In recent years, systems for processing environmental information have been evolving from research and development systems to practical applications. Today, many of these systems ...
Franz Josef Radermacher, Wolf-Fritz Riekert, Bernd...
—Probability models are estimated by use of penalized log-likelihood criteria related to AIC and MDL. The accuracies of the density estimators are shown to be related to the trad...
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
Performing distributed consensus in a network has been an important research problem for several years, and is directly applicable to sensor networks, autonomous vehicle formation...
Daniel Thai, Elizabeth Bodine-Baron, Babak Hassibi