In this paper we show the power of sampling techniques in designing efficient distributed algorithms. In particular, we show that using sampling techniques, on some networks, sele...
—A novel formulation for optimal sensor selection and in-network fusion for distributed inference known as the prizecollecting data fusion (PCDF) is proposed in terms of optimal ...
Animashree Anandkumar, Meng Wang, Lang Tong, Anant...
Abstract--A crucial issue in designing learning machines is to select the correct model parameters. When the number of available samples is small, theoretical sample-based generali...
Background: Numerous feature selection methods have been applied to the identification of differentially expressed genes in microarray data. These include simple fold change, clas...
Previous work has shown that robot navigation systems that employ an architecture based upon the idiotypic network theory of the immune system have an advantage over control techn...
Amanda M. Whitbrook, Uwe Aickelin, Jonathan M. Gar...