This paper presents algorithms for efficiently computing the covariance matrix for features that form sub-windows in a large multidimensional image. For example, several image proc...
Dimensionality reduction is an important problem in pattern recognition. There is a tendency of using more and more features to improve the performance of classifiers. However, not...
In this paper, the global optimization problem with an objective function that is multiextremal that satisfies the Lipschitz condition over a hypercube is considered. An algorithm...
Abstract. Most common feature selection techniques for document categorization are supervised and require lots of training data in order to accurately capture the descriptive and d...
Due to the shrinking of feature size and reduction in supply voltages, nanoscale circuits have become more susceptible to radiation induced transient faults. In this paper, we pre...