The existing reinforcement learning approaches have been suffering from the curse of dimension problem when they are applied to multiagent dynamic environments. One of the typical...
In this paper, we propose a new clustering procedure for high dimensional microarray data. Major difficulty in cluster analysis of microarray data is that the number of samples to ...
Segmentation is a popular technique for discovering structure in time series data. We address the largely open problem of estimating the number of segments that can be reliably di...
A modeling approach is presented that captures the dependence of the power dissipation of a combinational logic circuit on its input output signal switching activity. The resulting...
Algorithms such as Least Median of Squares (LMedS) and Random Sample Consensus (RANSAC) have been very successful for low-dimensional robust regression problems. However, the comb...