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Network topology inference from incomplete observation data

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References

  1. 1

    Rodriguez M G, Leskovec J, Krause A. Inferring networks of diffusion and influence. Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington DC, 2010. 1019–1028

  2. 2

    Rodriguez M G, Balduzzi D, Schölkopf B. Uncovering the temporal dynamics of diffusion networks. In: Proceedings of the 28th International Conference on Machine Learning, Bellevue, 2011. 561–568

  3. 3

    Amin K, Heidari H, Kearns M. Learning from contagion (without timestamps). In: Proceedings of the 31st International Conference on Machine Learning, Beijing, 2014. 1845–1853

  4. 4

    Sefer E, Kingsford C. Convex risk minimization to infer networks from probabilistic diffusion data at multiple scales. In: Proceedings of 2015 IEEE 31st International Conference, Seoul, 2015. 663–674

  5. 5

    Dou P, Du S Z, Song G J. Inferring diffusion network on incomplete cascade data. In: Proceedings of the 17th International Conference on Web-Age Information Management, Nanchang, 2016. 325–337

  6. 6

    Zong B, Wu Y H, Singh A K, et al. Inferring the underlying structure of information cascades. In: Proceedings of 2013 IEEE 13th International Conference on Data Mining, Brussels, 2012. 1218–1223

  7. 7

    Lokhov A Y. Reconstructing parameters of spreading models from partial observations. In: Proceedings of the 29th Conference on Neural Information Processing Systems, Barcelona, 2016. 3459–3467

  8. 8

    Kempe D, Kleinberg J, Tardos E. Maximizing the spread of influence through a social network. In: Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, 2003. 137–146

  9. 9

    Khuller S, Moss A, Naor J S. The budgeted maximum coverage problem. Inf Process Lett, 1999, 70: 39–45

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant No. 61572041), Beijing Natural Science Foundation (Grant No. 4152023), National High Technology Research and Development Program of China (863 Program) (Grant No. 2014AA015103).

Author information

Correspondence to Guojie Song.

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Supporting information Appendixes A–F. The supporting information is available online at info. scichina.com and link.springer.com. The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.

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Dou, P., Song, G. & Zhao, T. Network topology inference from incomplete observation data. Sci. China Inf. Sci. 61, 028102 (2018). https://doi.org/10.1007/s11432-017-9154-1

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