We consider the problem of collectively approximating a set of sensor signals using the least amount of space so that any individual signal can be efficiently reconstructed within...
Hierarchical clustering methods are widely used in various scientific domains such as molecular biology, medicine, economy, etc. Despite the maturity of the research field of hie...
We report a novel possibility for extracting a small subset of a data base which contains all the information necessary to solve a given classification task: using the Support Vec...
—We are now living in a world where information is growing and updating quickly. Knowledge can be acquired more efficiently with the help of automatic document summarization and...
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...