: A new supervised learning procedure for training RBF networks is proposed. It uses a pair of parallel running Kalman filters to sequentially update both the output weights and th...
Background: The SH3 domain family is one of the most representative and widely studied cases of so-called Peptide Recognition Modules (PRM). The polyproline II motif PxxP that gen...
: The consolidation of multiple servers and their workloads aims to minimize the number of servers needed thereby enabling the efficient use of server and power resources. At the s...
Daniel Gmach, Jerry Rolia, Ludmila Cherkasova, Gui...
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Traditional sensor network deployments consisted of fixed infrastructures and were relatively small in size. More and more, we see the deployment of ad-hoc sensor networks with h...
Martin F. O'Connor, Vincent Andrieu, Mark Roantree