817 search results - page 51 / 164 » Robust Euclidean embedding |
ICML
2007
IEEE
16 years 20 days ago
2007
IEEE
In many real-world applications, Euclidean distance in the original space is not good due to the curse of dimensionality. In this paper, we propose a new method, called Discrimina...
104
click to vote
STACS
2007
Springer
15 years 6 months ago
2007
Springer
: Hard metrics are the class of extremal metrics with respect to embedding into Euclidean spaces: they incur Ω(logn) multiplicative distortion, which is as large as it can possib...
ICMLA
2008
15 years 1 months ago
2008
A method is presented to partition a given set of data entries embedded in Euclidean space by recursively bisecting clusters into smaller ones. The initial set is subdivided into ...
139
click to vote
SDM
2007
SIAM
15 years 1 months ago
2007
SIAM
Nonlinear dimensionality reduction methods often rely on the nearest-neighbors graph to extract low-dimensional embeddings that reliably capture the underlying structure of high-d...
105
click to vote
NIPS
1997
15 years 1 months ago
1997
Nonlinear dimensionality reduction is formulated here as the problem of trying to find a Euclidean feature-space embedding of a set of observations that preserves as closely as p...