Multi-output learning via spectral filtering

Abstract

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

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