Multiple instance (MI) learning is a recent learning paradigm that is more flexible than standard supervised learning algorithms in the handling of label ambiguity. It has been u...
We present an ensemble learning approach that achieves accurate predictions from arbitrarily partitioned data. The partitions come from the distributed processing requirements of ...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...
Current research in biomedical informatics involves analysis of multiple heterogeneous data sets. This includes patient demographics, clinical and pathology data, treatment histor...
Srivatsava Ranjit Ganta, Jyotsna Kasturi, John Gil...
— Multicast-based data communication is an efficient communication scheme especially in multihop ad hoc networks where the MAC layer is based on one-hop broadcast from one sourc...
Abstract. We propose a brain-computer interface (BCI) system for evolving images in realtime based on subject feedback derived from electroencephalography (EEG). The goal of this s...