Graph classification using signal-subgraphs: Applications in statistical connectomics

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 35, Issue 7, 2013, Pages 1539-1551

  Vogelstein, Joshua T ^a   Roncal, William Gray ^b   Jacob Vogelstein, R ^b   Priebe, Carey E ^c  

^a DUKE UNIVERSITY   (United States)

^b JOHNS HOPKINS UNIVERSITY APPLIED PHYSICS LABORATORY   (United States)

^c Johns Hopkins University   (United States)

Author keywords

classification; connectome; graph theory; network theory; Statistical inference; structural pattern recognition

Indexed keywords

ASYMPTOTICALLY OPTIMAL; CONNECTOME; CONNECTOMICS; GRAPH CLASSIFICATION; STATISTICAL INFERENCE; STRUCTURAL PATTERN RECOGNITION; SYNTHETIC DATA; TRAINING SAMPLE;

CIRCUIT THEORY; CLASSIFICATION (OF INFORMATION); ESTIMATION; GRAPH THEORY; SAMPLING;

COMPUTER SIMULATION;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER SIMULATION; METHODOLOGY; REPRODUCIBILITY; STATISTICAL MODEL; THEORETICAL MODEL; THREE DIMENSIONAL IMAGING; PROCEDURES;

ALGORITHMS; COMPUTER SIMULATION; IMAGING, THREE-DIMENSIONAL; MODELS, STATISTICAL; MODELS, THEORETICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS;

EID: 84878132220     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2012.235     Document Type: Review

References (43)

1. H. Bunke and K. Riesen, "Towards the Unification of Structural and Statistical Pattern Recognition," Pattern Recognition Letters, vol. 33, no. 7, http://linkinghub.elsevier.com/retrieve/pii/S0167865511001309 http://www.sciencedirect.com/science/article/pii/S0167865511001309, pp. 811-825, May 2011.
2. P. Hagmann, L. Cammoun, X. Gigandet, S. Gerhard, P. Ellen Grant, V. Wedeen, R. Meuli, J.-P. Thiran, C.J. Honey, and O. Sporns, "MR Connectomics: Principles and Challenges," J. Neuroscience Methods, vol. 194, no. 1, http://www.ncbi.nlm.nih. gov/entrez/query.fcgi?cmd=Retrieve&db= PubMed&dopt= Citation&list-uids=20096730, pp. 34-45, 2010.
3. D.L.D. Donoho, M. Elad, and V.N.V. Temlyakov, "Stable Recovery of Sparse Overcomplete Representations in the Presence of Noise," IEEE Trans. Information Theory, vol. 52, no. 1, pp. 6-18, http://ieeexplore.ieee.org/xpl/ articleDetails.jsp?arnumber=1564423, Jan. 2006. (Pubitemid 43263116)
4. E.J. Candès and M. Wakin, "An Introduction to Compressive Sampling," IEEE Signal Processing Magazine, vol. 25, no. 2, pp. 21-30, Mar. 2008.
5. T. Kudo, "An Application of Boosting to Graph Classification," Science.
6. N.S. Ketkar, L.B. Holder, and D.J. Cook, "Empirical Comparison of Graph Classification Algorithms," Proc. IEEE Symp. Computational Intelligence and Data Mining, pp. 259-266, http://ieeexplore.ieee.org/lpdocs/ epic03/wrapper.htm?arnumber= 4938658, Mar. 2009.
7. G. North, Invertebrate Neurobiology, R.J.G. Geoffrey North, ed. CSHL Press, 2007.
8. J.D. Shepherd and R.L. Huganir, "The Cell Biology of Synaptic Plasticity: AMPA Receptor Trafficking," Ann. Rev. Cell and Developmental Biology, vol. 23, pp. 613-643, http://www.ncbi.nlm.nih.gov/pubmed/17506699, Jan. 2007.
9. J. Nolte, The Human Brain: An Introduction to Its Functional Anatomy. Mosby, 2002.
10. J.W. Lichtman, J. Livet, and J.R. Sanes, "A Technicolour Approach to the Connectome," Nature Rev. Neuroscience, vol. 9, no. 6, pp. 417-422, http://dx.doi.org/10.1038/nrn2391, June 2008.
11. D.S. Bassett and E.T. Bullmore, "Human Brain Networks in Health and Disease," Current Opinion in Neurology, vol. 22, no. 4, pp. 340-347, 2009.
12. J. Lasserre, C.M. Bishop, and T. Minka, "Principled Hybrids of Generative and Discriminative Models," Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 87-94, http://ieeexplore.ieee.org/lpdocs/ epic03/wrapper.htm?arnumber= 1640745, 2006. (Pubitemid 44931316)
13. P.J. Bickel and K.A. Doksum, Mathematical Statistics: Basic Ideas and Selected Topics, vol. 1, second ed. Prentice Hall, 2000.
14. C.M. Stein, "Inadmissibility of the Usual Estimator of the Mean of a Multivariate Normal Distribution," Proc. Third Berkeley Symp. Math. Statistics and Probability, pp. 197-206, 1956.
15. P.I. Good, Permutation, Parametric, and Bootstrap Tests of Hypotheses. Springer, 2010.
16. Q. McNemar, "Note on the Sampling Error of the Difference between Correlated Proportions or Percentages," Psychometrika, vol. 12, no. 2, pp. 153-157, June 1947.
17. P.J. Huber, Robust Statistics. Wiley, http://doi.wiley.com/10.1002/ 9780470434697, 1981.
18. J.A. Rice, Mathematical Statistics and Data Analysis. Duxbury Press, 1995.
19. D.J. Hand and K. Yu, "Idiot's Bayes: Not So Stupid After All?" Int'l J. Statistical Rev., vol. 69, no. 3, pp. 385-398, Nov. 2001. (Pubitemid 33392115)
20. R. Tibshirani, "Regression Shrinkage and Selection via the Lasso," J. Royal Statistical Soc., Series B, vol. 58, pp. 267-288, 1996.
21. B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani, "Least Angle Regression," Annals of Statistics, vol. 32, no. 2, pp. 407-499, 2004. (Pubitemid 41250302)
22. A.K. Jain, R.P.W. Duin, J. Mao, and S. Member, "Statistical Pattern Recognition: A Review," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 1, pp. 4-37, http://ieeexplore.ieee.org/lpdocs/ epic03/wrapper.htm?arnumber=824819, Jan. 2000. (Pubitemid 32132953)
23. O. Sporns, Networks of the Brain. The MIT Press, 2010.
24. J.T. Vogelstein, W.R. Gray, J.L. Prince, L. Ferrucci, S.M. Resnick, C.E. Priebe, and R.J. Vogelstein, "Graph-Theoretical Methods for Statistical Inference on MR Connectome Data," Organization Human Brain Mapping, 2010.
25. W.R. Gray, J.A. Bogovic, J.T. Vogelstein, B.A. Landman, J.L. Prince, and R.J. Vogelstein, "Magnetic Resonance Connectome Automated Pipeline: An Overview." IEEE Pulse, vol. 3, no. 2, pp. 42-48, http://ieeexplore.ieee. org/xpl/articleDetails.jsp? arnumber=6173097, Mar. 2010.
26. J.T. Vogelstein, R.J. Vogelstein, and C.E. Priebe, "Are Mental Properties Supervenient on Brain Properties?" Nature Scientific Reports, p. 11, 2011.
27. H. Pao, G.A. Coppersmith, C.E. Priebe, H.P. Ao, G.A.C. Oppersmith, and C.E.P. Riebe, "Statistical Inference on Random Graphs: Comparative Power Analyses via Monte Carlo," J. Computational and Graphical Statistics, 20, pp. 1-22, http://pubs.amstat.org/doi/abs/10.1198/jcgs.2010.09004, 2010.
28. C.E. Priebe, G.A. Coppersmith, and A. Rukhin, "You Say Graph Invariant, I Say Test Statistic," Statistical Computing Statistical Graphics Newsletter, vol. 21, no. 2, pp. 11-14, 2010.
29. A. Rukhin and C.E. Priebe, "A Comparative Power Analysis of the Maximum Degree and Size Invariants for Random Graph Inference," J. Statistical Planning and Inference, vol. 141, no. 2, pp. 1041-1046, 2011.
30. I.S. Dhillon, "Co-Clustering Documents and Words Using Bipartite Spectral Graph Partitioning," Proc. Seventh ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining, pp. 269-274, http://portal.acm.org/ citation.cfm?doid=502512.502550, 2001.
31. L. Devroye, L. Gyö rfi, G. Lugosi, and L. Gyorfi, A Probabilistic Theory of Pattern Recognition. Springer, 1996.
32. E.J. Candès and B. Recht, "Exact Matrix Completion via Convex Optimization," Foundations of Computational Math., vol. 9, no. 6, pp. 717-772, Apr. 2009.
33. X. Ding, L. He, and L. Carin, "Bayesian Robust Principal Component Analysis," Image, vol. 20, no. 12, pp. 3419-3430, 2011.
34. V. Chandrasekaran, S. Sanghavi, P.A. Parrilo, and A.S. Willsky, "Rank-Sparsity Incoherence for Matrix Decomposition," SIAM J. Optimization, vol. 21, no. 2, p. 572, June 2011.
35. P.D. Hoff, A.E. Raftery, and M.S. Handcock, "Latent Space Approaches to Social Network Analysis," J. Am. Statistical Assoc., vol. 97, no. 460, pp. 1090-1098, http://pubs.amstat.org/doi/abs/10.1198/016214502388618906, Dec. 2002. (Pubitemid 36136568)
36. D.L. Sussman, M. Tang, D.E. Fishkind, and C.E. Priebe, "A Consistent Dot Product Embedding for Stochastic Blockmodel Graphs," J. Am. Statistical Assoc., p. 17, 2012.
37. D.E. Fishkind, D.L. Sussman, M. Tang, J.T. Vogelstein, and C.E. Priebe, "Consistent Adjacency-Spectral Partitioning for the Stochastic Block Model When the Model Parameters Are Unknown," Rapid Post, http://arxiv.org/abs/ 1205.0309, p. 20, May 2012.
38. J.T. Vogelstein, J.C.M. Conroy, L.J. Podrazik, S.G. Kratzer, D.E. Fishkind, R.J. Vogelstein, and C.E. Priebe, "(Brain) Graph Matching via Fast Approximate Quadratic Programming," Rapid Post, 2011.
39. J.T. Vogelstein and C.E. Priebe, "Shuffled Graph Classification: Theory and Connectome Applications," arXiv:1112.5506v2[q-bio.QM] 2011.
40. G.A. Coppersmith and C.E. Priebe, "Vertex Nomination via Content and Context," Technology, pp. 1-21, 2012.
41. D.J. Marchette, C.E. Priebe, and G.A. Coppersmith, "Vertex Nomination via Attributed Random Dot Product Graphs," 2011.
42. D.S. Lee and C.E. Priebe, "Bayesian Vertex Nomination," Rapid Post, 2012.
43. D.D. Bock, W.-C.A. Lee, A.M. Kerlin, M.L. Andermann, A.W. Wetzel, S. Yurgenson, E.R. Soucy, H.S. Kim, G. Hood, and R.C. Reid, "Network Anatomy and in Vivo Physiology of Visual Cortical Neurons," Nature, vol. 471, no. 7337, pp. 177-182, Mar. 2011.