Approximating Higher-Order Distances Using Random Projections

Details Approximating Higher-Order Distances Using Random Projections Approximating Higher-Order Distances Using Random Projections

2012-03-15

arxiv.org/abs/1203.3492v1

Computer Science

Learning

Appears in Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (UAI2010)

Scientific paper

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.

Affiliated with

Also associated with

No associations

Rating

Approximating Higher-Order Distances Using Random Projections does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Approximating Higher-Order Distances Using Random Projections, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Approximating Higher-Order Distances Using Random Projections will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-32215