A Note on Perturbation Results for Learning Empirical 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 alg...
| Main Authors: | , , |
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2008
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| Online Access: | http://hdl.handle.net/1721.1/41940 |