221 search results - page 35 / 45 » On Approximating the Radii of Point Sets in High Dimensions |
76
Voted
NIPS
2008
14 years 11 months ago
2008
This paper introduces a new approach to constructing meaningful lower dimensional representations of sets of data points. We argue that constraining the mapping between the high a...
MICRO
2006
IEEE
15 years 4 months ago
2006
IEEE
Designing and optimizing high performance microprocessors is an increasingly difficult task due to the size and complexity of the processor design space, high cost of detailed si...
174
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SIGMOD
2009
ACM
15 years 10 months ago
2009
ACM
The skyline of a d-dimensional dataset consists of all points not dominated by others. The incorporation of the skyline operator into practical database systems necessitates an ef...
97
Voted
NIPS
2007
14 years 11 months ago
2007
We propose a novel method for linear dimensionality reduction of manifold modeled data. First, we show that with a small number M of random projections of sample points in RN belo...
83
Voted
CVPR
2008
IEEE
16 years 8 days ago
2008
IEEE
We consider the task of dimensionality reduction for regression (DRR) whose goal is to find a low dimensional representation of input covariates, while preserving the statistical ...