Clustering is ill-defined. Unlike supervised learning where labels lead to crisp performance criteria such as accuracy and squared error, clustering quality depends on how the cl...
Rich Caruana, Mohamed Farid Elhawary, Nam Nguyen, ...
The explosive growth of the vision data motivates the recent studies on efficient data indexing methods such as locality-sensitive hashing (LSH). Most existing approaches perform...
Clustering can be defined as a data assignment problem where the goal is to partition the data into nonhierarchical groups of items. In our previous work, we suggested an informati...
Background: Image analysis is the first crucial step to obtain reliable results from microarray experiments. First, areas in the image belonging to single spots have to be identif...
In this paper, we introduce and study the Minimum Consistent Subset Cover (MCSC) problem. Given a finite ground set X and a constraint t, find the minimum number of consistent sub...
Byron J. Gao, Martin Ester, Jin-yi Cai, Oliver Sch...