Mining relational data often boils down to computing clusters, that is finding sub-communities of data elements forming cohesive sub-units, while being well separated from one an...
With rapid increase of parallel computation systems in their sizes, it is inevitable to develop algorithms that are applicable even if there exist faulty elements in the systems. ...
We present an incremental algorithm for building a neighborhood graph from a set of documents. This algorithm is based on a population of artificial agents that imitate the way re...
Density estimation with Gaussian Mixture Models is a popular generative technique used also for clustering. We develop a framework to incorporate side information in the form of e...
In floorplan design, it is common that a designer will want to control the positions of some modules in the final packing for various purposes like data path alignment, I/O connec...