Multi-output learning via spectral filtering


In this paper we study a class of regularized kernel methods for multi-output learning which are based on filtering the spectrum of the kernel matrix. The considered methods include Tikhonov regularization as a special case, as well as interesting alternatives such as vector-valued extensions of L2 boosting and other iterative schemes. Computational… (More)
DOI: 10.1007/s10994-012-5282-y


13 Figures and Tables

Slides referencing similar topics