References
- Angulo, J. and Serra, J. (2007). Modelling and segmentation of colour images in polar representations,(4): 475-495.
- Äyrämö, S. (2006)., Ph.D. thesis, University of Jyväskylä, Jyväskylä.
- Bagirov, A.M. and Ugon, J. (2005). An algorithm for minimizing clustering functions,(4-5): 351-368.
- Bagirov, A.M., Ugon, J. and Webb, D. (2011). Fast modified global-means algorithm for incremental cluster construction,(4): 886-876.
- Bezdek, J.C. (1981)., Kluwer Academic Publishers, Norwell, MA.
- Boyd, D.L. and Vandenberghe, L. (2004)., Cambridge University Press, Cambridge.
- Chaovalitwongse, W.A., Butenko, S. and Pardalos, P.M., (Eds.) (2009)., World Scientific, London.
- Choulakian, V. (2001). Robust q-mode principal component analysis in1,,(2): 135-150.
- Clarke, F. H., (1990)., SIAM, Philadelphia, PA.
- Cominetti, R. and Michelot, C. (1997 ). Sufficient conditions for coincidence in1-minisum multifacility location problems,(4): 179-185.
- Cord, A., Ambroise, C. and Cocquerez, J.-P. (2006 ). Feature selection in robust clustering based on Laplace mixture,(6): 627-635.
- Cupec, R., Grbi´c, R., Sabo, K. and Scitovski, R. (2009). Three points method for searching the best least absolute deviations plane,(3): 983-994.
- Duda, R., Hart, P. and Stork, D. (2001)., Wiley, New York, NY.
- Finkel, D.E. and Kelley, C.T. (2006). Additive scaling and the DIRECT algorithm,(4): 597-608.
- Floudas, C.A. and Gounaris, C.E. (2009). A review of recent advances in global optimization,(4): 3-38.
- Frąckiewicz, M. and Palus, H. (2011). KHM clustering techique as a segmentation method for endoscopic colour images,(1): 203-209, DOI: 10.2478/v10006-011-0015-0.
- Gan, G., Ma, C. and Wu, J. (2007)., SIAM, Philadelphia, PA.
- Grbić, R., Nyarko, E.K. and Scitovski, R. (2012). A modification of the direct method for Lipschitz global optimization for a symmetric function,,(4): 1193-1212, DOI: 10.1007/s10898-012-0020-3.
- Grbić , R., Scitovski, K., Sabo, K. and Scitovski, R. (2013). Approximating surfaces by the moving least absolute deviations method,(9): 4387-4399.
- Gurwitz, C. (1990). Weighted median algorithms for1 approximation,(2): 301-310.
- Hathaway, R.J. and Bezdek, J.C. (2001). Fuzzy-means clustering of incomplete data,(5): 735-744.
- Hubert, L. and Arabie, P. (1985). Comparing partitions,(1): 193-218.
- Jain, A. (2010). 50 years beyond-means,(8): 651-666.
- Jajuga, K. (1987). A clustering method based on the1-norm,(4): 357-371.
- Jajuga, K. (1991).1-norm based fuzzy clustering,(1): 43-50.
- Iyigun, C. (2007)., Ph.D. thesis, Graduate School, Rutgers, New Brunswick, NJ.
- Jones, D.R., Perttunen, C.D. and Stuckman, B.E. (1993).
- Lipschitzian optimization without the Lipschitz constant,(1): 157-181.
- Jörnsten, R. (2004). Clustering and classification based on the1 data depth,(1): 67-89.
- Kogan, J. (2007)., Cambridge University Press, Cambridge.
- Leisch, F. (2006). A toolbox for-centroids cluster analysis,(2): 526-544.
- Li, X. Hu, W., Wang, H. and Zhang, Z. (2010). Linear discriminant analysis using rotational invariant1 norm,(13-15): 2571-2579.
- Scitovski, R. and Scitovski, S. (2013). A fast partitioning algorithm and its application to earthquake investigation,(1): 124-131.
- Simiński, K. (2012). Neuro-rough-fuzzy approach for regression modelling from missing data,(2): 461-476, DOI: 10.2478/v10006-012-0035-4.
- Späth, H. (1976).1-cluster analysis,(4): 379-387.
- Späth, H. (1987). Using the1-norm within cluster analysis,Y. Dodge (Ed.),1, Elsevier, Amsterdam, pp. 427-434.
- Malinen, M.I. and Fränti, P. (2012). Clustering by analytic functions,(1): 31-38.
- Meng, D., Zhao, Q and Xu, Z. (2012). Improve robustness of sparse PCA by1-norm maximization,(1): 487-497.
- Pintér, J.D. (1996)., Kluwer Academic Publishers, Dordrecht.
- Ruszczynski, A (2006)., Princeton University Press, Princeton/Oxford, NJ.
- Sabo, K. and Scitovski, R. (2008). The best least absolute deviations line-properties and two efficient methods,(2): 185-198.
- Sabo, K., Scitovski, R. and Vazler, I. (2011). Searching for a best LAD-solution of an overdetermined system of linear equations motivated by searching for a best LAD-hyperplane on the basis of given data,(2): 293-314.
- Sabo, K., Scitovski, R. and Vazler, I. (2012). One-dimensional center-based1-clustering method,(1): 5-22
- Sabo, K., Scitovski, R., Vazler, I. and Zeki´c-Sušac, M. (2011). Mathematical models of natural gas consumption,(3): 1721-1727.
- Teboulle, M. (2007). A unified continuous optimization framework for center-based clustering methods,(1): 65-102.
- Vardi, Y., Zhang, C. H. (2000). The multivariate1-median and associated data depth,(4): 1423-1426.
- Vazler, I., Sabo, K. and Scitovski, R. (2012). Weighted median of the data in solving least absolute deviations problems,(8): 1455-1465.
- Zhang, J., Peng, L., Zhao, X. and Kuruoglu E.E. (2012 ). Robust data clustering by learning multi-metric-norm distances,(1): 335-349.
Language: English
Page range: 151 - 163
Published on: Mar 25, 2014
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
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© 2014 Kristian Sabo, published by University of Zielona Góra
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