1. MacQueen, J.: Some methods for classification and analysis of multivariate observations. In: Le Cam, L.M., Neyman, J. (eds.) Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281–297. University of California Press, Berkeley (1967)

   Google Scholar 

2. Jain, A.K., Murty, M.N., Flynn, P.J.: Data clustering: A review. ACM Computing Surveys 31(3), 264–323 (1999)

   Article  Google Scholar 

3. Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann Publishers, inc, San mateo (1988)

   Google Scholar 

4. Kschischang, F.R., Frey, B.J., Loeliger, H.A.: Factor graphs and the sum-product algorithm. IEEE Transactions on Information Theory 47(2), 498–519 (2001)

   Article MathSciNet MATH  Google Scholar 

5. Aji, S.M., McEliece, R.J.: The generalized distributive law. IEEE Transactions on Information Theory 46(2), 325–343 (2000)

   Article MathSciNet MATH  Google Scholar 

6. Yedidia, J.S., Freeman, W.T., Weiss, Y.: Constructing free-energy approximations and generalized belief propagation algorithms. IEEE Transactions on Information Theory 51(7), 2282–2312 (2005)

   Article MathSciNet  Google Scholar 

7. Frey, B.J., Dueck, D.: Clustering by passing messages between data points. Science 315 (2007)

   Google Scholar 

8. Teitz, M.B., Bart, P.: Heuristic methods for estimating the generalized vertex median of a weighted graph. Operations Research 16(5), 955–961 (1968)

   Article MATH  Google Scholar 

9. Tansel, B.C., Francis, R.L., Lowe, T.J.: Location on networks: A survey; part I: Thep-center andp-median problems. Management Science 29(4), 482–497 (1983)

   Article MathSciNet MATH  Google Scholar 

10. Hansen, P., Mladenović, N.: Variable neighborhood search for thep-median. Location Science 5(4), 207–226 (1997)

    Article MATH  Google Scholar 

11. Lashkari, D., Golland, P.: Convex clustering with exemplar-based models. In: Platt, J., Koller, D., Singer, Y., Roweis, S. (eds.) Advances in Neural Information Processing Systems 20, pp. 825–832. MIT Press, Cambridge (2008)

    Google Scholar 

12. Leone, M., Weigt, M.: Clustering by soft-constraint affinity propagation: Applications to gene-expression data. Bioinformatics 23, 2708 (2007)

    Article  Google Scholar 

13. Mézard, M.: Where are the exemplars? Science 315, 949–951 (2007)

    Article  Google Scholar 

14. Lin, S., Kernighan, B.W.: An effective heuristic algorithm for the traveling salesman problem. Operations Research 21, 498–516 (1973)

    Article MathSciNet MATH  Google Scholar 

15. Mézard, M.: Passing messages between disciplines. Science 301(5640), 1685–1686 (2003)

    Article  Google Scholar 

16. Handler, G.Y., Mirchandani, P.B.: Location on Networks: Theory and Algorithms. MIT Press, Cambridge (1979)

    MATH  Google Scholar 

17. Li, W., Xu, L., Schuurmans, D.: Facility locations revisited: An efficient belief propagation approach. In: Proceedings of the 2010 IEEE International Conference on Automation and Logistics (2010)

    Google Scholar 

18. Li, W.: Probabilistic inference over sensor networks for clusters: Extension to multiple states. In: Proceedings of the 2012 IEEE International Conference on Information and Automation (2012)

    Google Scholar 

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