We address the problem of integrating objects from a source taxonomy into a master taxonomy. This problem is not only currently pervasive on the web, but also important to the eme...
We present a randomized coloring algorithm for the unstructured radio network model, a model comprising autonomous nodes, asynchronous wake-up, no collision detection and an unkno...
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Observed in many applications, there is a potential need of extracting a small set of frequent patterns having not only high significance but also low redundancy. The significance...