Approximating Higher-Order Distances Using Random Projections
Ping Li, Michael W. Mahoney, Yiyuan She · arXiv (Cornell University) · 2012
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 2 is known to be difficult. Our work partially fills this gap.