Kernel functions as similarity measures for sequential data have been extensively studied in previous research. This contribution addresses the efficient computation of distance fu...
In the k-medoid problem, given a dataset P, we are asked to choose k points in P as the medoids. The optimal medoid set minimizes the average Euclidean distance between the points ...
We develop a multi-class object detection framework whose core component is a nearest neighbor search over object part classes. The performance of the overall system is critically...
The recent explosion in distance learning programs on the world-wide web has spawned a lively debate on the future and the potential of these programs. While distance learning wil...
In this paper we show how game theory and Gibbs sampling techniques can be used to design a self-optimizing algorithm for minimizing end-to-end delays for all flows in a multi-clas...