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DAGM
2010
Springer

Random Fourier Approximations for Skewed Multiplicative Histogram Kernels

10 years 20 days ago
Random Fourier Approximations for Skewed Multiplicative Histogram Kernels
Abstract. Approximations based on random Fourier features have recently emerged as an efficient and elegant methodology for designing large-scale kernel machines [4]. By expressing the kernel as a Fourier expansion, features are generated based on a finite set of random basis projections with inner products that are Monte Carlo approximations to the original kernel. However, the original Fourier features are only applicable to translation-invariant kernels and are not suitable for histograms that are always non-negative. This paper extends the concept of translation-invariance and the random Fourier feature methodology to arbitrary, locally compact Abelian groups. Based on empirical observations drawn from the exponentiated 2 kernel, the state-of-the-art for histogram descriptors, we propose a new group called the skewedmultiplicative group and design translation-invariant kernels on it. Experiments show that the proposed kernels outperform other kernels that can be similarly approxima...
Fuxin Li, Catalin Ionescu, Cristian Sminchisescu
Added 08 Nov 2010
Updated 08 Nov 2010
Type Conference
Year 2010
Where DAGM
Authors Fuxin Li, Catalin Ionescu, Cristian Sminchisescu
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