To date, many active learning techniques have been developed for acquiring labels when training data is limited. However, an important aspect of the problem has often been neglect...
Abstract: The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like ...
Time-series of count data are generated in many different contexts, such as web access logging, freeway traffic monitoring, and security logs associated with buildings. Since this...
Background: The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of gene...
Pedro Carmona-Saez, Roberto D. Pascual-Marqui, Fra...
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...