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This paper introduces a simple yet powerful data transformation strategy for kernel machines. Instead of adapting the parameters of the kernel function w.r.t. the given data (as in conventional methods), we adjust both the kernel hyper-parameters and the given data itself. Using this approach, the input data is transformed to be more representative of the assumptions encoded in the kernel function...
Making precise predictions about the future behavior of a system such as a country's economy, a firm or a lake, or about the population of some species of animal has always been a challenge. While prediction methods and modeling procedures have been developed and used over the past decades, the high degree of uncertainty and complexity that underlie some systems makes it difficult, and in some cases...
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