Document clustering techniques mostly rely on single term analysis of the document data set, such as the Vector Space Model. To better capture the structure of documents, the unde...
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
Background: Most non-coding RNA families exert their function by means of a conserved, common secondary structure. The Rfam data base contains more than five hundred structurally ...
The quadtree data structure is widely used in digital image processing and computer graphics for modeling spatial segmentation of images and surfaces. A quadtree is a tree in whic...
Laurent Balmelli, Jelena Kovacevic, Martin Vetterl...
Estimating geometric structure from uncalibrated images accurately enough for high quality rendering is difficult. We present a method where only coarse geometric structure is trac...