Feature space perspectives for learning the kernel1
نویسندگان
چکیده
In this paper, we continue our study of learning the kernel. We present a reformulation of this problem within a feature space environment. This leads us to study regularization in the dual space of all continuous functions on a compact domain with values in a Hilbert space with a mix norm. We also relate this problem in a special case to regularization. 1This work was supported by NSF Grant ITR-0312113 and EPSRC Grant GR/T18707/01.
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