Attribute fusion in a latent process model for time series of graphs

IEEE Transactions on Signal Processing

Volumn 61, Issue 7, 2013, Pages 1721-1732

  Tang, Minh ^a   Park, Youngser ^b   Lee, Nam H ^a   Priebe, Carey E ^a  

^a JOHNS HOPKINS UNIVERSITY   (United States)

^b Johns Hopkins University   (United States)

Author keywords

Anomaly detection; Attributed random graphs; Random dot product graphs

Indexed keywords

ANOMALY DETECTION; APPROXIMATION MODEL; CATEGORICAL ATTRIBUTES; HYPOTHESIS TESTING; LATENT PROCESS MODELS; PRODUCT GRAPH; RANDOM GRAPHS; SECOND-ORDER APPROXIMATION;

BRAIN; GRAPHIC METHODS; SOCIAL NETWORKING (ONLINE); TEXT PROCESSING; TIME SERIES;

GRAPH THEORY;

EID: 84897584295     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2013.2243445     Document Type: Article

References (29)

1. N. H. Lee and C. E. Priebe, "A latent process model for time series of attributed random graphs," Statist. Inference Stoch. Process., vol. 14, pp. 231-253, 2011.
2. D. K. Hammond, P. Vandergheynst, and R. Gribonval, "Wavelets on graphs via spectral graph theory," Appl. Comput. Harmon. Anal., vol. 30, pp. 129-150, 2010.
3. R. R. Coifman andM.Maggioni, "Diffusion wavelets," Appl. Comput. Harmon. Anal., vol. 21, pp. 53-94, 2006. (Pubitemid 43947621)
4. M. Crovella and E. D. Kolaczyk, "Graph wavelets for spatial traffic analysis," in Proc. 22nd Annu. Joint Conf. IEEE Comput. Commun. Soc., 2003, pp. 1848-1857.
5. S. K. Narang and A. Ortega, "Perfect reconstruction two-channel wavelet filter-baks for graph structured data," IEEE Trans. Signal Process., vol. 60, no. 6, pp. 2786-2799, 2012.
6. B. A. Miller, N. T. Bliss, and P. J. Wolfe, "Toward signal processing theory for graphs and non-Euclidean data," in Proc. 35th IEEE Int. Conf. Acoust., Speech, Signal Process., 2010, pp. 5414-5417.
7. C. E. Priebe, N. H. Lee, Y. Park, and M. Tang, "Attribute fusion in a latent process model for time series of graphs," in Proc. IEEE Workshop Statist. Signal Process., Nice, France, Jun. 28-30, 2011, pp. 513-516.
8. P. Erdös and A. Rényi, "On random graphs," PublicationesMathematicae, vol. 6, pp. 290-297, 1959.
9. P.W. Holland and S. Leinhardt, "An exponential family of probability distributions for directed graphs," J. Amer. Statist. Assoc., vol. 76, pp. 33-50, 1981.
10. P. Holland, K. Laskey, and S. Leinhardt, "Stochastic blockmodels: First steps," Social Netw., vol. 5, no. 2, pp. 109-137, 1983.
11. Y. J. Wang and G. Y. Wong, "Stochastic blockmodels for directed graphs," J. Amer. Statist. Assoc., vol. 82, no. 397, pp. 8-19, 1987.
12. P. Hoff, A. E. Raftery, and J. M. Tantrum, "Latent space approaches to social network analysis," J. Amer. Statist. Assoc., vol. 97, pp. 1090-1098, 2002. (Pubitemid 36136568)
13. S. Young and E. Scheinerman, "Random dot product models for social networks," in Proc. 5th Int. Conf. Algorithms Models Web-Graph, 2007, pp. 138-149.
14. A. Rukhin and C. E. Priebe, "A comparative power analysis of the maximum degree and size invariants for random graph inference," J. Statist. Planning Inference, vol. 141, pp. 1041-1046, 2011.
15. E. Airoldi, D. Blei, S. Fienberg, and E. Xing, "Mixed membership stochastic blockmodels," J. Mach. Learn. Res., vol. 9, pp. 1981-2014, 2008.
16. S. Asmussen, Applied Probability and Queues. NewYork,NY,USA: Springer-Verlag, 2003.
17. D. J. Marchette and C. E. Priebe, "Predicting unobserved links in incompletely observed networks," Comput. Statist. Data Anal., vol. 52, pp. 1373-1386, 2008. (Pubitemid 350007781)
18. E. R. Scheinerman and K. Tucker, "Modeling graphs using dot product representations," Comput. Statist., vol. 25, pp. 1-16, 2010.
19. D. L. Sussman,M. Tang, D. E. Fishkind, and C. E. Priebe, "Aconsistent adjacency spectral embedding for stochastic blockmodel graphs," J. Amer. Statist. Assoc., vol. 107, pp. 1119-1128, 2012.
20. N. Heard, D. Weston, K. Platanioti, and D. Hand, "Bayesian anomaly detection methods for social networks," Ann. Appl. Statist., vol. 4, pp. 645-662, 2010.
21. P. O. Perry and P. J. Wolfe, "Point process modelling for directed interaction networks," J. Roy. Statist. Soc. Ser. B, to be published.
22. C. E. Priebe, J. M. Conroy, D. J. Marchette, and Y. Park, "Scan statistics on Enron graphs," Comput. Math. Organizat. Theory, vol. 11, pp. 229-247, 2005. (Pubitemid 43118968)
23. H. Pao, G. A. Coppersmith, and C. E. Priebe, "Statistical inference on random graphs: Comparative power analyses via Monte Carlo," J. Comput. Graph. Statist., vol. 20, pp. 395-416, 2011.
24. K. Nowicki and J. C. Wierman, "Subgraph counts in random graphs using incomplete -statistics methods," Discrete Math., vol. 72, pp. 299-310, 1988.
25. A. Rukhin, "Asymptotic analysis of various statistics for random graph inference," Ph.D. dissertation, The Johns Hopkins Univ., Baltimore, MD, USA, 2009.
26. B. Bollobás, Random Graphs. New York, NY, USA: Academic, 1985.
27. A. Rukhin and C. E. Priebe, "On the limiting distribution of a graph scan statistic," Commun. Statist.: Theory and Methods, vol. 41, pp. 1151-1170, 2012.
28. C. E. Priebe, G. C. Coppersmith, and A. Rukhin, "You say graph invariant, I say test statistic," Statist. Comput. Graph. Newslett., vol. 21, pp. 11-14, 2010.
29. M. W. Berry, M. Browne, and B. Signer, 2001 Topic Annotated Enron Email Data Set. Philadelphia, PA, USA: Linguistic Data Consortium, 2001.