The representation used by a learning algorithm introduces a bias which is more or less well-suited to any given learning problem. It is well known that, across all possible probl...
As various genome sequencing projects have already been completed or are near completion, genome researchers are shifting their focus from structural genomics to functional genomi...
Abstract. The purpose of this paper is (1) to provide a theoretical justification for the use of Monte-Carlo sampling for approximate resolution of NP-hard maximization problems in...
: One way to scale up clustering algorithms is to squash the data by some intelligent compression technique and cluster only the compressed data records. Such compressed data recor...
We present an algorithm for automatically classifying the interior and exterior parts of a polygonal model. The need for visualizing the interiors of objects frequently arises in ...