Existing approaches to analyzing the asymptotics of graph Laplacians typically assume a well-behaved kernel function with smoothness assumptions. We remove the smoothness assumpti...
This paper proposes the use of constructive ordinals as mistake bounds in the on-line learning model. This approach elegantly generalizes the applicability of the on-line mistake ...
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Many of today's best classification results are obtained by combining the responses of a set of base classifiers to produce an answer for the query. This paper explores a nov...
VT-ASOS is a framework for holistic and continuous customization of system software on HPC systems. The framework leverages paravirtualization technology. VT-ASOS extends the Xen ...
Dimitrios S. Nikolopoulos, Godmar Back, Jyotirmaya...