Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
A fundamental problem when computing statistical shape models is the determination of correspondences between the instances of the associated data set. Often, homologies between po...
Heike Hufnagel, Xavier Pennec, Jan Ehrhardt, Heinz...
This paper studies scalable data delivery algorithms in mobile ad hoc sensor networks with node and link failures. Many algorithms have been developed for data delivery and fusion...
Bin Yu, Paul Scerri, Katia P. Sycara, Yang Xu, Mic...
Many large -scale spatial data analysis problems involve an investigation of relationships in heterogeneous databases. In such situations, instead of making predictions uniformly a...
Aleksandar Lazarevic, Dragoljub Pokrajac, Zoran Ob...
Redescription mining is a newly introduced data mining problem that seeks to find subsets of data that afford multiple definitions. It can be viewed as a generalization of associa...