Random Projection Trees Revisited

Details Random Projection Trees Revisited Random Projection Trees Revisited

2010-10-19

arxiv.org/abs/1010.3812v2

Computer Science

Data Structures and Algorithms

Accepted for publication at NIPS 2010. This version corrects an incorrect usage of the term Assouad dimension - acknowledgment

Scientific paper

The Random Projection Tree structures proposed in [Freund-Dasgupta STOC08] are space partitioning data structures that automatically adapt to various notions of intrinsic dimensionality of data. We prove new results for both the RPTreeMax and the RPTreeMean data structures. Our result for RPTreeMax gives a near-optimal bound on the number of levels required by this data structure to reduce the size of its cells by a factor $s \geq 2$. We also prove a packing lemma for this data structure. Our final result shows that low-dimensional manifolds have bounded Local Covariance Dimension. As a consequence we show that RPTreeMean adapts to manifold dimension as well.

Affiliated with

Also associated with

No associations

Rating

Random Projection Trees Revisited 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 Random Projection Trees Revisited, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Random Projection Trees Revisited will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-268358