@article{eprints1710,
           pages = {197--210},
          number = {2},
          volume = {4},
            year = {2010},
           title = {Error bounds for suboptimal solutions to kernel principal component analysis},
          author = {Giorgio Gnecco and Marcello Sanguineti},
       publisher = {Springer},
         journal = {Optimization Letters},
        keywords = {Principal component analysis (PCA); Kernel methods; Suboptimal solutions},
        abstract = {Suboptimal solutions to kernel principal component analysis are considered. Such solutions take on the form of linear combinations of all n-tuples of kernel functions centered on the data, where n is a positive integer smaller than the cardinality m of the data sample. Their accuracy in approximating the optimal solution, obtained in general for n = m, is estimated. The analysis made in Gnecco and Sanguineti (Comput Optim Appl 42:265?287, 2009) is extended. The estimates derived therein for the approximation of the first principal axis are improved and extensions to the successive principal axes are derived.},
             url = {http://eprints.imtlucca.it/1710/}
}