In this paper we propose an approach to address the old problem of identifying the feature conditions under which a gaming strategy can be effective. For doing this, we will build ...
Chad Hogg, Stephen Lee-Urban, Bryan Auslander, H&e...
Given a pair of images represented using bag-of-visual words and a label corresponding to whether the images are “related”(must-link constraint) or “unrelated” (must not li...
We introduce tiered clustering, a mixture model capable of accounting for varying degrees of shared (context-independent) feature structure, and demonstrate its applicability to i...
We use clustering to derive new relations which augment database schema used in automatic generation of predictive features in statistical relational learning. Clustering improves...
Document clustering is a very hard task in Automatic Text Processing since it requires to extract regular patterns from a document collection without a priori knowledge on the cat...