A critical problem in implementing interactive perception applications is the considerable computational cost of current computer vision and machine learning algorithms, which typ...
Padmanabhan Pillai, Lily B. Mummert, Steven W. Sch...
Clustering ensembles has been recently recognized as an emerging approach to provide more robust solutions to the data clustering problem. Current methods of clustering ensembles ...
Existing supercomputers have hundreds of thousands of processor cores, and future systems may have hundreds of millions. Developers need detailed performance measurements to tune ...
Todd Gamblin, Bronis R. de Supinski, Martin Schulz...
Huge amounts of data are available in large-scale networks of autonomous data sources dispersed over a wide area. Data mining is an essential technology for obtaining hidden and v...
Mei Li, Guanling Lee, Wang-Chien Lee, Anand Sivasu...
Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
Risheng Liu, Zhouchen Lin, Fernando De la Torre, Z...