Averaging of kernel functions

ESANN 2012 proceedings, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

Volumn , Issue , 2012, Pages 363-368

  Belanche, Lluís A ^a   Tosi, Alessandra ^a  

^a UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; NEURAL NETWORKS;

FLEXIBLE LEARNING; HARMONIC MEAN; KERNEL FUNCTION; KERNEL LEARNING; MULTIPLE KERNEL LEARNING; POSITIVE REAL; ROOT MEAN SQUARE; WEIGHTED MEAN;

LEARNING SYSTEMS;

EID: 84947773007     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (7)

1. Shawe-Taylor, J., Cristianini, N. Kernel Methods for Pattern Analysis. Cambridge Univ. Press, 2004.
2. Vapnik, V.N. The nature of Statical Learning Theory. Springer, New York, 1995.
3. Hille, E. Methods in Classical and Functional Analysis. Addison-Wesley, 1971.
4. Hardy, G., Littlewood, J.E., Pölya, G. Inequalities. Cambridge Univ. Press, 1952.
5. FitzGerald, C., Micchelli, C., Pinkus, A. Functions that preserve families of positive semidefinite matrices. Linear Algebra & its Applications 221: 83-102, 1995.
6. Krantz, S.G. Function theory of several complex variables. Wadsworth and Brooks/Cole Advanced Books and Software, Second edition, 1992.
7. Bach, F. R., Lanckriet, G. R. G., Jordan, M. I. Multiple kernel learning, conic duality, and the SMO algorithm. International Conference on Machine Learning (pp. 6-13), 2004.