Kernels and Regularization on Graphs
Abstract
We introduce a family of kernels on graphs based on the notion of regularization operators. This generalizes in a natural way the notion of regularization and Greens functions, as commonly used for real valued functions, to graphs. It turns out that diffusion kernels can be found as a special case of our reasoning. We show that the class of positive, monotonically decreasing functions on the unit interval leads to kernels and corresponding regularization operators.
Cite
Text
Smola and Kondor. "Kernels and Regularization on Graphs." Annual Conference on Computational Learning Theory, 2003. doi:10.1007/978-3-540-45167-9_12Markdown
[Smola and Kondor. "Kernels and Regularization on Graphs." Annual Conference on Computational Learning Theory, 2003.](https://mlanthology.org/colt/2003/smola2003colt-kernels/) doi:10.1007/978-3-540-45167-9_12BibTeX
@inproceedings{smola2003colt-kernels,
title = {{Kernels and Regularization on Graphs}},
author = {Smola, Alexander J. and Kondor, Risi},
booktitle = {Annual Conference on Computational Learning Theory},
year = {2003},
pages = {144-158},
doi = {10.1007/978-3-540-45167-9_12},
url = {https://mlanthology.org/colt/2003/smola2003colt-kernels/}
}