Kernel pls variants for regression, in

Abstract. We focus on covariance criteria for finding a suitable subspace for regression in a reproducing kernel Hilbert space: kernel principal component analysis, kernel partial least squares and kernel canonical correlation analysis, and we demonstrate how this fits within a more general context of subspace regression. For the kernel partial least squares case some variants are considered and the methods are illustrated and compared on a number of examples.

Sequential Learning with LS-SVM for Large-Scale Data Sets

Peer reviewe

Nanoparticulate Tungsten Oxide for Catalytic Epoxidations

A combination of spectroscopic and catalytic investigations led to the surprising conclusion that not isolated WVI species but WO3 oxide is the most active and stable phase for olefin epoxidation with H2O2. Optimal activity was subsequently found for a nanoparticulate WO3 prepared by flame aerosol technology. This material is characterized by a 50% increase in activity per WVI site, and a 35-fold increase in space time yield, compared with the current benchmark catalyst