We present an (1+ε)-approximation algorithm for computing the minimum-spanning tree of points in a planar arrangement of lines, where the metric is the number of crossings betwee...
Many important problems involve clustering large datasets. Although naive implementations of clustering are computationally expensive, there are established efficient techniques f...
We study the problem of clustering uncertain objects whose locations are uncertain and described by probability density functions. We analyze existing pruning algorithms and experi...
A technique for clustering data by common attribute values involves grouping rows and columns of a binary matrix to make the minimum number of submatrices all 1’s. As binary mat...
Doina Bein, Linda Morales, Wolfgang W. Bein, C. O....
Abstract. This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an ...