Sciweavers

Share
JMLR
2010

On Learning with Integral Operators

8 years 2 months ago
On Learning with Integral Operators
A large number of learning algorithms, for example, spectral clustering, kernel Principal Components Analysis and many manifold methods are based on estimating eigenvalues and eigenfunctions of operators defined by a similarity function or a kernel, given empirical data. Thus for the analysis of algorithms, it is an important problem to be able to assess the quality of such approximations. The contribution of our paper is two-fold:
Lorenzo Rosasco, Mikhail Belkin, Ernesto De Vito
Added 28 Jan 2011
Updated 28 Jan 2011
Type Journal
Year 2010
Where JMLR
Authors Lorenzo Rosasco, Mikhail Belkin, Ernesto De Vito
Comments (0)
books