We discuss the problem of learning to rank labels from a real valued feedback associated with each label. We cast the feedback as a preferences graph where the nodes of the graph ...
The increasing availability of network data is creating a great potential for knowledge discovery from graph data. In many applications, feature vectors are given in addition to g...
Arash Rafiey, Flavia Moser, Martin Ester, Recep Co...
Correlation mining has gained great success in many application domains for its ability to capture underlying dependencies between objects. However, research on correlation mining ...
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
In object-oriented systems, runtime memory is composed of an object graph in which objects refer to other objects. This graph of objects evolves while the system is running. Graph...