This work deals with the distributed measurement and reconstruction of time-varying spatial fields using wireless sensor networks (WSN). We use basis functions to formulate a low...
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
We explore the possibilities to organize a query data structure in the main memories or hard disks of a cluster computer. The query data structure serves to improve the performanc...
Recent theoretical results have shown that improved bounds on generalization error of classifiers can be obtained by explicitly taking the observed margin distribution of the trai...
We report the results of fitting mixture models to the distribution of expression values for individual genes over a broad range of normal tissues, which we call the marginal expr...