Information Theory, Machine Learning, and Reproducing Kernel Hilbert Spaces-Reference-Cited by-同舟云学术

Information Theory, Machine Learning, and Reproducing Kernel Hilbert Spaces

Published:2010 Issue: Volume: Page:1-45
ISSN:1613-9011
Container-title:Information Theoretic Learning
language:
Short-container-title:

Author:

Principe José C.

Publisher

Springer New York

Link

http://link.springer.com/content/pdf/10.1007/978-1-4419-1570-2_1

Reference63 articles.

1. Aczél J., Daróczy Z., On measures of information and their characterizations, Mathematics in Science and Engineering, vol. 115, Academic Press, New York, 1975.

2. Aronszajn N., The theory of reproducing kernels and their applications, Cambridge Philos. Soc. Proc., vol. 39:133–153, 1943.

3. Aronszajn N., Theory of reproducing kernels, Trans. of the Amer. Math. Soc., 68(3):337–404, 1950.

4. Berlinet A., Thomas-Agnan C., Reproducing Kernel Hilbert Spaces in Probability and Statistics, Kluwer, Norwell, MA, 2003.

5. Bregman L.M. (1967). The relaxation method of finding the common points of convex sets and its application to the solution of problems in convex programming. USSR Comput. Math. Math. Phys. 7:200–217.

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