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High-Dimensional Data

Link Prediction for Partially Observed Networks

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Pages 725-733 | Received 01 Sep 2015, Published online: 07 Jul 2017

References

  • Adamic, L. A., and Adar, E. (2003), “Friends and Neighbors on the Web,” Social Networks, 25, 211–230.
  • Balachandran, P., Airoldi, E., and Kolaczyk, E. (2013), “Inference of Network Summary Statistics Through Network Denoising,” Annals of Statistics, arXiv:1310.0423.
  • Balachandran, P., Kolaczyk, E. D., and Viles, W. (2014), “On the Propagation of Low-Rate Measurement Error to SubgraphCounts in Large,” Sparse Networks, arXiv:1409.5640.
  • Ben-Hur, A., and Noble, W. S. (2005), “Kernel Methods for Predicting Protein-Protein Interactions,” Bioinformatics, 21, i38–i46.
  • ——— (2006), “Choosing Negative Examples for the Prediction ofProtein-Protein Interactions,” BMC Bioinformatics, 7, (Suppl 1):S2.
  • Bleakley, K., Biau, G., and Vert, J.-P. (2007), “Supervised Reconstruction of Biological Networks With Local Models,” Bioinformatics, 23, i57–i65.
  • Boyd, S., and Vandenberghe, L. (2004), Convex Optimization, New York: Cambridge University Press.
  • Clauset, A., Moore, C., and Newman, M. E. J. (2008), “Hierarchical Structure and the Prediction of Missing Links in Networks,” Nature, 453, 98–101.
  • Getoor, L., and Diehl, C. P. (2005), “Link Mining: A Survey,” ACM SIGKDD Explorations Newsletter, 7, 3–12.
  • Hasan, M. A., Chaoji, V., Salem, S., and Zaki, M. (2006), “Link Prediction Using Supervised Learning,” in Workshop on Link Analysis, Counter-terrorism and Security (at SIAM Data Mining Conference).
  • Hasan, M. A., and Zaki, M. J. (2011), “A Survey of Link Prediction in Social Networks,” in Social Network Data Analytics, ed. C. C. Aggarwal, New York: Springer, pp. 243–275.
  • Hildreth, C. (1957), “A Quadratic Programming Procedure,” Naval ResearchLogistics Quarterly, 4, 79–85.
  • Hoff, P. D. (2007), “Modeling Homophily and Stochastic Equivalence in Symmetric Relational Data,” in Advances in Neural InformationProcessing Systems (vol. 19), Cambridge, MA: MIT Press, pp. 657--664.
  • ——— (2009), “Multiplicative Latent Factor Models for Description and Prediction of Social Networks,” Computational & Mathematical Organization Theory, 15, 261–272.
  • Hoff, P. D., Raftery, A. E., and Handcock, M. S. (2002), “Latent Space Approaches to Social Network Analysis,” Journal of the American Statistical Association, 97, 1090–1098.
  • Hunter, D. R., Goodreau, S. M., and Handcock, M. S. (2008), “Goodness of Fit of Social Network Models,” Journal of the American Statistical Association, 103, 248–258.
  • Kashima, H., Kato, T., Yamanishi, Y., Sugiyama, M., and Tsuda, K. (2009), “Link Propagation: A Fast Semi-Supervised Learning Algorithm for Link Prediction,” in Proceedings of the 2009SIAM International Conference on Data Mining, 1100--1111.
  • Katz, L. (1953), “A New Status Index Derived From Sociometric Analysis,” Psychometrika, 18, 39–43.
  • Leicht, E. A., Holme, P., and Newman, M. E. J. (2006), “Vertex Similarity in Networks,” Physical Review E, 73, 026120.
  • Liben-Nowell, D., and Kleinberg, J. (2007), “The Link-Prediction Problem for Social Networks,” Physica A: Statistical Mechanics and its Applications, 390, 1150–1170.
  • Lu, L., and Zhou, T. (2010), “Link Prediction in Complex Networks: A Survey,” arXiv:1010.0725v1.
  • Luo, Z.-Q., and Tseng, P. (1992), “On the Convergence of the Coordinate Descent Method for Convex Differentiable Minimization,” Journal of Optimization Theory and Applications, 72, 7–35.
  • Menon, A., and Elkan, C. (2011), “Link Prediction via Matrix Factorization,” in Machine Learning and Knowledge Discovery in Databases, (Lecture Notes in Computer Science, Vol. 6912), eds. D. Gunopulos, T. Hofmann, D. Malerba, and M. Vazirgiannis, Berlin Heidelberg: Springer, pp. 437–452.
  • Miller, K., Griffiths, T., and Jordan, M. (2009), “Nonparametric Latent Feature Models for Link Prediction,” in Advances in Neural Information Processing Systems (NIPS) (Vol. 22), eds. Y. Bengio, D. Schuurmans, J. Lafferty, and C. Williams, Red Hook, NY: Curran Associates, pp. 1276--1284.
  • Priebe, C. E., Sussman, D. L., Tang, M., and Vogelstein, J. T. (2015), “Statistical Inference on Errorfully Observed Graphs,” Journal of Computational and Graphical Statistics, 24, 930–953.
  • Raymond, R., and Kashima, H. (2010), “Fast and Scalable Algorithms for Semi-Supervised Link Prediction on Static and Dynamic Graphs,” in Machine Learning and Knowledge Discovery in Databases (Lecture Notes in Computer Science, Vol. 6323), eds. J. Balczar, F. Bonchi, A. Gionis, and M. Sebag, Berlin Heidelberg: Springer, pp. 131–147.
  • von Mering, C., Krause, R., Snel, B., Cornell, M., Oliver, S. G., Fields, S., and Bork, P. (2002), “Comparative Assessment of Large-Scale Data Sets of Protein-Protein Interactions,” Nature, 417, 399–403.
  • Warga, J. (1963), “Minimizing Certain Convex Functions,” Journal of the Society for Industrial and Applied Mathematics, 11, 588–593.
  • Yang, Y., Chawla, N., Sun, Y., and Hani, J. (2012), “Predicting Links in Multi-Relational and Heterogeneous Networks,” in 2012 IEEE 12th International Conference on Data Mining (ICDM), pp. 755–764.
  • Yu, K., Chu, W., Yu, S., Tresp, V., and Xu, Z. (2007), “Stochastic Relational Models for Discriminative Link Prediction,” in Proceedings of Neural Information Processing Systems, Cambridge MA: MIT Press, pp. 1553–1560.

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