B. Sch\"olkopf, A. Smola, and K.-R. M\"uller (1998)
Nonlinear component analysis as a kernel Eigenvalue problem
Neural Computation, 10:1299–1319.
Applies the kernel method to unsupervised algorithms as for instance Principal Component Analysis. This gives a principled and efficient approach to nonlinear PCA.
Technical Report No. 44, 1996, Max Planck Institut für biologische Kybernetik, Tübingen