In this paper we describe a new cluster model which is based on the concept of linear manifolds. The method identifies subsets of the data which are embedded in arbitrary oriented...
We consider the computational problem of finding nearest neighbors in general metric spaces. Of particular interest are spaces that may not be conveniently embedded or approximate...
According to dramatically growing interesting in power-efficient embedded processor, designers must establish the proper power strategy when they design new embedded processor core...
Let F be a collection of n d-variate, possibly partially defined, functions, all algebraic of some constant maximum degree. We present a randomized algorithm that computes the vert...
This paper studies automatic segmentation of multiple
motions from tracked feature points through spectral embedding
and clustering of linear subspaces. We show that
the dimensi...