Reproducing Kernel Hilbert Spaces Associated with Analytic Translation-Invariant Mercer Kernels

By Hongkai Sun, Ding-Xuan Zhou. 2008

34 citations recorded by the source corpus.

Subfields: Applied Mathematics, Artificial Intelligence, Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Applied Mathematics

1. Ernesto De Vito
2. Alessandro Toigo
3. Veronica Umanità
4. Claudio Carmeli
5. Lorenzo Rosasco
6. Bharath K. Sriperumbudur
7. Kenji Fukumizu
8. Alessandro Verri

In Artificial Intelligence

1. Ernesto De Vito
2. Veronica Umanità
3. Alessandro Toigo
4. Claudio Carmeli

In Computer Vision and Pattern Recognition

1. Ernesto De Vito
2. Veronica Umanità
3. Alessandro Toigo
4. Claudio Carmeli

Citations in the corpus

• Vector valued reproducing kernel Hilbert spaces and universality (2008, methodology): “In learning theory, reproducing kernel Hilbert spaces (RKHS) are an important tool for designing learning algorithms, see for example [8, 29, 31] and the book [9].”