397 search results - page 8 / 80 » Local embeddings of metric spaces |
NIPS
1997
13 years 10 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...
STOC
2005
ACM
14 years 9 months ago
2005
ACM
A low-distortion embedding between two metric spaces is a mapping which preserves the distances between each pair of points, up to a small factor called distortion. Low-distortion...
ICML
2007
IEEE
14 years 9 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...
DAC
2006
ACM
14 years 9 months ago
2006
ACM
Since performance on FPGAs is dominated by the routing architecture rather than wirelength, we propose a new architecture-aware approach to initial FPGA placement that models the ...
SODA
2007
ACM
13 years 10 months ago
2007
ACM
This paper addresses the basic question of how well can a tree approximate distances of a metric space or a graph. Given a graph, the problem of constructing a spanning tree in a ...