Let
In the (special) smoothing spline problem one considers a variational problem with a quadratic data fidelity penalty and Laplacian regularization. Higher order regularity can be obtained via replacing the Laplacian regulariser with a poly-Laplacian regulariser. The methodology is readily adapted to graphs and here we consider graph poly-Laplacian regularization in a fully supervised, non-parametric, noise corrupted, regression problem. In particular, given a dataset
- Award ID(s):
- 2005797
- NSF-PAR ID:
- 10475993
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Sampling Theory, Signal Processing, and Data Analysis
- Volume:
- 21
- Issue:
- 2
- ISSN:
- 2730-5716
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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