We study a novel hierarchical wireless networking approach in which some of the nodes are more capable than others. In such networks, the more capable nodes can serve as Mobile Ba...
We describe a new LLL-type algorithm, H-LLL, that relies on Householder transformations to approximate the underlying Gram-Schmidt orthogonalizations. The latter computations are ...
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 ...
Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black...
—This paper presents an operational rate-distortion (ORD) optimal approach for skeleton-based boundary encoding. The boundary information is first decomposed into skeleton and di...
Haohong Wang, Guido M. Schuster, Aggelos K. Katsag...