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arXiv · 1203.3492

Approximating Higher-Order Distances Using Random Projections

Ping Li·Michael W. Mahoney·Yiyuan She
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Abstract

We provide a simple method and relevant theoretical analysis for efficiently estimating higher-order lp distances. While the analysis mainly focuses on l4, our methodology extends naturally to p = 6,8,10..., (i.e., when p is even). Distance-based methods are popular in machine learning. In large-scale applications, storing, computing, and retrieving the distances can be both space and time prohibitive. Efficient algorithms exist for estimating lp distances if 0 < p <= 2. The task for p > 2 is known to be difficult. Our work partially fills this gap.

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BibTeXRIS

Ping Li, Michael W. Mahoney, Yiyuan She. 2012-03-15. Approximating Higher-Order Distances Using Random Projections. https://arxiv.org/abs/1203.3492

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