Sparse Kernel Approximations for Efficient Classification and Detection

Efficient learning with non-linear kernels is often based on extracting features from the data that linearise the kernel. While most constructions aim at obtaining low-dimensional and dense features, in this work we explore high-dimensional and sparse ones. We give a method to compute sparse feature...

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Bibliografische gegevens
Hoofdauteurs: Vedaldi, A, Zisserman, A, IEEE
Formaat: Journal article
Taal:English
Gepubliceerd in: 2012