منابع
[1] Ng, A.Y., Jordan, M., and Weiss, Y., 2002, On
spectral clustering: analysis and an algorithm:
Advances in Neural Information Processing Systems,
14.
[2] Tenenbaum, J.B., deSilva, V., and Langford, J.C.,
2000, A global geometric framework for nonlinear
dimensionality reduction: Science, 290, p. 2319–2323.
[3] Roweis, S.T and Saul, L.K., 2000, Nonlinear
dimensionality reduction by locally linear embedding:
Science, 290, p. 2323–2326.
[4] Zhang , T., et al., 2008, A unifying framework for
spectral analysis based dimensionality reduction: in
IEEE World Congress on Computational Intelligence.
[5] Chung, F.R.K., 1997, Spectral Graph Theory:
CBMS Regional Conference Series in Mathematics, 92.
5
6
ب مُه محمدی، اب اًلقاسم کامکار ریحاوی وشری علمی_پژی شَی م ىُدسی
معدن
01
[6] Müller, K.R., et al., 2001, An introduction to kernelbased
learning algorithms: Neural Networks, IEEE
Transaction on, 12(2), p. 181–202.
[7] Schölkopf, B. and A.J. Smola., 2002, Learning with
Kernels, Support Vector Machines, Regularization,
Optimization, and Beyond: Cambridge, MA, USA, MIT
Press.
[8] Donath, W.E and Hoffman, A.J., 1973, Lower
bounds for the partitioning of graphs: IBM J. Res.
Develop, Vol. 17, No. 5, pp. 420-425.
[9] TREMBLAY, N., PUY, G., GRIBONVAL, R.,
VANDERGHEYNST, P., 2016, Compressive Spectral
Clustering: Proceedings of the 33 rd International
Conference on Machine Learning, New York, NY,
USA, JMLR: W&CP volume 48.
[10] von Luxburg, U., 2007, A tutorial on spectral
clustering: Statistics and Computing, 17, 395–416.
[11] Auffarth, B., 2007, Spectral Graph Clustering:
Universitat de Barcelona, course report for T´ecnicas
Avanzadas de Aprendizaje at Universitat Politecnica de
Catalunya.
[12] Hadjighasem, A., Karrasch, D., Teramoto, H.,
Haller, G., 2016, Spectral-clustering approach to
Lagrangian vortex detection: PHYSICAL REVIEW E
93, 063107.
[13] Wu, S., Feng, X., Zhou, W., 2014, Spectral
clustering of high-dimensional data exploiting sparse
representation vectors: Neurocomputing 135, 229–239.
[14] Scott, G.L. and Longuet-Higgins, H.C., 1990,
Feature grouping by relocalisation of eigenvectors of
the proxmity matrix: in British Machine Vision
Conference, p. 103-108.
[15] Perona, P. and Freeman, W.T., 1998, A
factorization approach to grouping: in ECCV.
[16] Shi, J., and Malik, J., 2000, Normalized cuts and
image segmentation: IEEE Transactions on Pattern
Analysis and Machine Intelligence, 22, 888–905.
[17] Meila, M., and Shi, J., 2001, Learning
segmentation by random walks: Leen, T.K., Dietterich,
T. G., and Tresp, V., eds., Advances in neural
information processing systems 13, MIT Press, 873–
879.
[18] Zelnik-Manor, L., and Perona, P., 2005, Self-tuning
spectral clustering: Saul, L. K., Weiss, Y., and Bottou,
L., eds., Advances in neural information processing
systems 17, MIT Press, 1601–1608.
[19] Zhang, X., Jiao, L., Liu, F., Bo, L., and Gong, M.,
2008, Spectral clustering ensemble applied to SAR
image segmentation: IEEE Transactions on Geoscience
and Remote Sensing, 46, 2126–2136.
[20] Zhou, H., 1997, Determination of velocities and
interfaces by multi-scale tomography: 67th Ann.
Internat. Mtg, Society of Exploration Geophysicists,
Expanded Abstracts, pp.1877-1880.
[21] Zhou, H., 2003, Multi-scale traveltime
tomography: Geophysics, 68, pp.1639-1649.
[22] Lehmann, B., 2007, Seismic travel time
tomography for еnginееring and ехрlоrаtiоn
аррliсаtiоns: EAGE Publications bv, pp.14.
[23] Loke M.H., Barker, R.D., 1996a, Rapid leastsquare
inverson of apparent resistivity pseudosections
using a quasi-Newton method: Geophysical Prospecting,
44, 131-152
[24] Loke, M.H., 2004, Tutorial: 2-D and 3-D electrical
imaging surveys.
[25] Desgraupes, B., 2013, Clustering Indices:
University Paris Ouest, Lab Modal’X.
[26] Kanaan, EL.B., Fadi, EL.F., Ashour, W., 2014,
Spectral Clustering Using Optimized Gaussian Kernel
Function: International Journal of Artificial Intelligence
and Applications for Smart Devices, Vol.2 , No.1, pp.
41-56.
[27] Hachmoler, B., Paasche, H., 2013, Integration of
surface-based tomographic models for zonation and
multimodel guided extrapolation of sparsely known
petrophysical parameters: GEOPHYSICS, VOL.78,
NO.4, PP43-53.
[28] West, D., 2007, Introduction to graph theory:
Prentice Hall.
