Unsupervised Kernel Function Building Using Maximization of Information Potential Variability

Author:

Álvarez-Meza A. M.,Cárdenas-Peña D.,Castellanos-Dominguez Germán

Publisher

Springer Berlin Heidelberg

Reference13 articles.

1. Belanche, L.: Developments in kernel design. In: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN, pp. 369–378 (2013)

2. Jenssen, R., Principe, J.C., Eltoft, T.: Information cut and information forces for clustering. In: NNSP, pp. 459–468 (September 2003)

3. Liu, W., Principe, J.C., Haykin, S.: Kernel Adaptive Filtering: A Comprehensive Introduction, vol. 57. John Wiley & Sons (2011)

4. Morejon, R.A., Principe, J.C.: Advanced search algorithms for information-theoretic learning with kernel-based estimators, 874–884 (2004)

5. Ng, A.Y., Jordan, M.I., Weiss, Y.: On Spectral Clustering: Analysis and an algorithm. Advances in Neural Information Processing Systems 14 (2001)

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