The supervised learning paradigm assumes in general that both training and test data are sampled from the same distribution. When this assumption is violated, we are in the setting...
Sparse wireless sensor networks (WSNs) are being effectively used in several applications, which include transportation, urban safety, environment monitoring, and many others. Sens...
Mario Di Francesco, Kunal Shah, Mohan Kumar, Giuse...
Transfer learning can be described as the tion of abstract knowledge from one learning domain or task and the reuse of that knowledge in a related domain or task. In categorizatio...
Kevin R. Canini, Mikhail M. Shashkov, Thomas L. Gr...
We present an approach for the supervised online learning of object representations based on a biologically motivated architecture of visual processing. We use the output of a rece...