Efficient Framework for Partitioning Positive Hypergraph into Dense Subgraph
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Akanksha J. Kulkarni, Swati A. Bhavsar, ”A Survey on Hypergraph
Partitioning Techniques,” International Journal of Trend in Research and
Development (IJTRD), ISSN: 2394-9333, Volume-4 — Issue-1 , February
B. Kernighan and S. Lin, ”An efficient heuristic procedure for partitioning
graphs,” Bell Syst. Tech. J., vol. 49, pp. 291-307, 1970.
D.-H. Huang and A. B. Kahng, ”When clusters meet partitions: New
density-based methods for circuit decomposition,” in Proc. Eur. Conf.
Des. Test,1995, pp. 60-64.
I. Dhillon, Y. Guan, and B. Kulis, ”Kernel k-means: spectral clustering
and normalized cuts,” in Proc. ACM Int. Conf. Knowl. Discov. Data Min.,
, pp. 551-556.
P. F. Felzenszwalb and D. P. Huttenlocher, ”Efficient graph-based Image
segmentation,” Int. J. Comput. Vis., vol. 59, no. 2, pp. 167-181, 2004
J. H. Kappes, M. Speth, B. Andres, G. Reinelt, and C. Schn, ”Globally
optimal image partitioning by multicuts,” in Proc. Energy Minim.
Methods Comput. Vis. Pattern Recognit., 2011, pp. 31-44.
C. Fiduccia and R. Mattheyses, ”A linear-time heuristic for improving
network partitions,” in Proc. 19th Conf. Des. Autom., 1982, pp. 175-181.
G. Karypis and V. Kumar, ”A fast and high quality multilevel scheme for
partitioning irregular graphs,” SIAM J. Sci. Comput., vol. 20, no. 1, pp.
-392, 1998.
N. Bansal, A. Blum, and S. Chawla, ”Correlation clustering,” Mach.
Learn., no. 1-3, vol. 56, pp. 89-113, 2004.
S. Kim, S. Nowozin, P. Kohli, and C. D. Yoo, ”Higher-order correlation
clustering for image segmentation,” in Proc. Adv. Neural Inf. Process.
Syst.,2011, pp. 1530-1538.
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