34 search results - page 2 / 7 » Embedding metric spaces in their intrinsic dimension |
FOCS
2003
IEEE
13 years 9 months ago
2003
IEEE
The doubling constant of a metric space (X, d) is the smallest value λ such that every ball in X can be covered by λ balls of half the radius. The doubling dimension of X is the...
SODA
2008
ACM
13 years 6 months ago
2008
ACM
We consider the problem of embedding a metric into low-dimensional Euclidean space. The classical theorems of Bourgain, and of Johnson and Lindenstrauss say that any metric on n p...
Publication
We consider the computational problem of finding nearest neighbors in general metric spaces. Of particular interest are spaces that may not be conveniently embedded or approximate...
FOCS
2005
IEEE
13 years 10 months ago
2005
IEEE
We consider the problem of embedding finite metrics with slack: we seek to produce embeddings with small dimension and distortion while allowing a (small) constant fraction of al...
CORR
2008
Springer
13 years 4 months ago
2008
Springer
Maximum Variance Unfolding (MVU) and its variants have been very successful in embedding data-manifolds in lower dimensionality spaces, often revealing the true intrinsic dimensio...