396 search results - page 20 / 80 » Lossy Reduction for Very High Dimensional Data |
RSS
2007
14 years 11 months ago
2007
Abstract— This paper considers the problem of learning to recognize different terrains from color imagery in a fully automatic fashion, using the robot’s mechanical sensors as ...
SODA
2000
ACM
14 years 10 months ago
2000
ACM
In this paper we give approximation algorithms for several proximity problems in high dimensional spaces. In particular, we give the rst Las Vegas data structure for (1 + )-neares...
79
Voted
CVPR
2008
IEEE
15 years 11 months ago
2008
IEEE
Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...
BMVC
2010
14 years 7 months ago
2010
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
RSS
2007
14 years 11 months ago
2007
Abstract— We consider the task of omnidirectional path following for a quadruped robot: moving a four-legged robot along any arbitrary path while turning in any arbitrary manner....