Manifold clustering, which regards clusters as groups of points around compact manifolds, has been realized as a promising generalization of traditional clustering. A number of lin...
In previous work, we have proposed a novel approach to data clustering based on the explicit optimization of a partitioning with respect to two complementary clustering objectives ...
In data clustering, many approaches have been proposed such as K-means method and hierarchical method. One of the problems is that the results depend heavily on initial values and...
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
Given the pairwise affinity relations associated with a set of data items, the goal of a clustering algorithm is to automatically partition the data into a small number of homogen...