Classifying high-dimensional numerical data is a very challenging problem. In high dimensional feature spaces, the performance of supervised learning methods suffer from the curse...
—This paper considers feature selection for data classification in the presence of a huge number of irrelevant features. We propose a new feature selection algorithm that addres...
Abstract--As multicore processors are deployed in mainstream computing, the need for software tools to help parallelize programs is increasing dramatically. Data-dependence profili...
Control of variability and performance in the back end of the VLSI manufacturing line has become extremely difficult with the introduction of new materials such as copper and low...
Yu Chen, Andrew B. Kahng, Gabriel Robins, Alexande...
: Traditional state modeling techniques have several limitations. One of these is the reduced ability to model a large number of variables simultaneously. Another limitation is tha...
Gregory Vert, Sergiu M. Dascalu, Frederick C. Harr...