Nonlinear projection with the isotop method

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2415 LNCS, Issue , 2002, Pages 933-938

  Lee, John A ^a   Verleysen, Michel ^a  

^a UNIVERSITÉ CATHOLIQUE DE LOUVAIN   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

NEURAL NETWORKS; PIECEWISE LINEAR TECHNIQUES; TOPOLOGY; CLUSTERING ALGORITHMS;

DATA SPACE; HIGH DIMENSIONAL DATA; NEURAL UNITS; NONLINEAR PROJECTIONS; PIECEWISE LINEAR; PROJECTION SPACE; REAL DATA SETS; TOPOLOGY PRESERVATION; HEIDELBERG;

CLUSTERING ALGORITHMS; TOPOLOGY;

EID: 84902177938     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-46084-5_151     Document Type: Conference Paper

References (14)

1. A. Ahalt, A. K. Krishnamurthy, P. Chen, and D. E. Melton. Competitive learning algorithms for vector quantization. Neural Network, 3:277-290, 1990.
2. C. L. Blake and C. J. Merz. UCI repository of machine learning databases, 1998.
3. P. Demartines and J. Hérault. Vector Quantization and Projection Neural Network. In A. Prieto, J. Mira, and J. Cabestany, editors, Lecture Notes in Computer Science, volume 686, pages 328-333. Springer-Verlag, 1993.
4. P. Demartines and J. Hérault. Curvilinear Component Analysis: A self-organizing neural network for nonlinear mapping of data sets.IEEE Transaction on Neural Networks, 8(1):148-154, January 1997.
5. E. W. Dijkstra. A note on two problems in connection with graphs.Numerical Mathematics, (1):269-271, 1959.
6. I. T. Jollife. Principal Component Analysis. Springer-Verlag, New York, 1986.
7. T. Kohonen. Self-organization of topologically correct feature maps.Biological Cybernetics, 43:59-69, 1982.
8. T. Kohonen. Self-Organizing Maps. Springer, Heidelberg, 2nd edition, 1995.
9. J. A. Lee, A. Lendasse, N. Donckers, and M. Verleysen. A Robust Nonlinear Projection Method. In M. Verleysen, editor, Proceedings ofESANN'2000, 8th European Symposium on Artificial Neural Networks, pages 13-20. D-Facto public., Bruges (Belgium), April 2000.
10. H. Ritter, T. Martinetz, and K. Schulten. Neural Computation and Self-Organizing Maps. Addison-Wesley, 1992.
11. W. Sammon, J. A nonlinear mapping algorithm for data structure analysis. IEEE Transactions on Computers, CC-18(5):401-409, 1969.
12. R. N. Shepard. The analysis of proximities: Multidimensional Scaling with an unknown distance function. Psychometrika, 27:125-140, 1962.
13. J. B. Tenenbaum, V. de Silva, and J. C. Langford. A global geometric framework for nonlinear dimensionality reduction. Science, 290(5500):2319-2323, 2000.
14. C. Von Der Malsburg. Self-organization of orientation sensitive cells in the striate cortex.Kybernetik, 14:85-100, 1973.