We propose a new transductive learning algorithm for learning optimal linear representations that utilizes unlabeled data. We pose the problem of learning linear representations a...
Classification of microarray data requires the selection of a subset of relevant genes in order to achieve good classification performance. Several genetic algorithms have been d...
Classical data mining algorithms implicitly assume complete access to all data, either in centralized or federated form. However, privacy and security concerns often prevent sharin...
A patient-specific seizure prediction algorithm is proposed that extracts novel multivariate signal coherence features from ECoG recordings and classifies a patient’s pre-seiz...
James R. Williamson, Daniel W. Bliss, David W. Bro...
A novel algorithm is proposed to learn pattern similarities for texture image retrieval. Similar patterns in di erent texture classes are grouped into a cluster in the feature spac...