In many clustering applications, the user has some vague notion of the number and membership of the desired clusters. However, it is difficult for the user to provide such knowled...
Anil K. Jain, Pavan Kumar Mallapragada, Martin H. ...
This paper studies an adaptive clustering problem. We focus on re-clustering an object set, previously clustered, when the feature set characterizing the objects increases. We prop...
We present a general framework for the construction of vertex orderings for netlist clustering. Our WINDOW algorithm constructs an ordering by iteratively adding the vertex with h...
In this paper a novel and generic approach for model-based data clustering in a boosting framework is presented. This method uses the forward stagewise additive modeling to learn t...
— In the last decade, graph-cut optimization has been popular for a variety of labeling problems. Typically graph-cut methods are used to incorporate smoothness constraints on a ...