— In this paper we are concerned with developing more reliable model reduction algorithms. We have focused on less common, but real, examples that fail to be effectively reduced ...
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...
Abstract-- This paper proposes a state reduction algorithm for incompletely specified FSMs. The algorithm is based on iterative improvements. When the number of compatibles is like...
In this paper, we propose a novel component-wise smoothing algorithm that constructs a hierarchy (or family) of smoothened log-likelihood surfaces. Our approach first smoothens th...
We obtain the following results related to dynamic versions of the shortest-paths problem: (i) Reductions that show that the incremental and decremental singlesource shortest-paths...