817 search results - page 51 / 164 » Robust Euclidean embedding |
ICML
2007
IEEE
15 years 10 months 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...
STACS
2007
Springer
15 years 3 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
14 years 11 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 ...
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SDM
2007
SIAM
14 years 11 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...
NIPS
1997
14 years 11 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...