Active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. In the past, simple ac...
The dramatic growth in the number and size of on-line information sources has fueled increasing research interest in the incremental subspace learning problem. In this paper, we pr...
We study three new techniques which will speed up the branch-and-bound algorithm for the MAX-2-SAT problem: The first technique is a new lower bound function for the algorithm an...
This paper summarizes the design and implementation of a parallel algorithm for state assignment of large Finite State Machines (FSMs). High performance CAD tools are necessary to...
Using SQL has not been considered an efficient and feasible way to implement data mining algorithms. Although this is true for many data mining, machine learning and statistical a...