Detecting changes in spatial datasets is important for many fields. In this paper, we introduce a methodology for change analysis in spatial datasets that combines contouring algor...
Christoph F. Eick, Chun-Sheng Chen, Michael D. Twa...
Distributed partially observable Markov decision problems (POMDPs) have emerged as a popular decision-theoretic approach for planning for multiagent teams, where it is imperative f...
The computation of covariance and correlation matrices are critical to many data mining applications and processes. Unfortunately the classical covariance and correlation matrices...
James Chilson, Raymond T. Ng, Alan Wagner, Ruben H...
Nucleation phenomena play a pivotal role in many atmospheric and technological processes. However, understanding atmospheric nucleation processes has been difficult due to the lac...
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...