The present paper analyzes the usefulness of the normalized compression distance for the problem to cluster the hemagglutinin (HA) sequences of influenza virus data for the HA gene...
We use cluster analysis as a unifying principle for problems from low, middle and high level vision. The clustering problem is viewed as graph partitioning, where nodes represent ...
The discovery of complex patterns such as clusters, outliers, and associations from huge volumes of streaming data has been recognized as critical for many domains. However, patte...
— We study the problem of building an optimal network-layer clustering hierarchy, where the optimality can be defined using three potentially conflicting metrics: state, delay ...
Leonid B. Poutievski, Kenneth L. Calvert, Jim Grif...
Clustering under constraints is a recent innovation in the artificial intelligence community that has yielded significant practical benefit. However, recent work has shown that fo...