On the sample mean of graphs

— We present an analytic and geometric view of the sample mean of graphs. The theoretical framework yields efficient subgradient methods for approximating a structural mean and a simple plug-in mechanism to extend existing central clustering algorithms to graphs. Experiments in clustering protein structures show the benefits of the proposed theory.

• Type: Conference
• Year: 2008
• Where: IJCNN
• Authors: Brijnesh J. Jain, Klaus Obermayer
• Keywords: Artificial Intelligence, Central Clustering Algorithms, Efficient Subgradient Methods, IJCNN 2008, Theoretical Framework Yields