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arXiv · 1704.04522

Hierarchic Kernel Recursive Least-Squares

Hossein Mohamadipanah·Mahdi Heydari·Girish Chowdhary
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Abstract

We present a new kernel-based algorithm for modeling evenly distributed multidimensional datasets that does not rely on input space sparsification. The presented method reorganizes the typical single-layer kernel-based model into a deep hierarchical structure, such that the weights of a kernel model over each dimension are modeled over its adjacent dimension. We show that modeling weights in the suggested structure leads to significant computational speedup and improved modeling accuracy.

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Hossein Mohamadipanah, Mahdi Heydari, Girish Chowdhary. 2017-04-14. Hierarchic Kernel Recursive Least-Squares. https://arxiv.org/abs/1704.04522

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