583 search results - page 53 / 117 » On small blocking sets and their linearity |
NIPS
2007
13 years 10 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...
CORR
2010
Springer
13 years 8 months ago
2010
Springer
Abstract: The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like ...
COLT
2004
Springer
14 years 2 months ago
2004
Springer
Abstract— We prove that given a nearly log-concave distribution, in any partition of the space to two well separated sets, the measure of the points that do not belong to these s...
ICIP
2002
IEEE
14 years 1 months ago
2002
IEEE
In this paper we present a method to estimate in real-time the position and orientation of a previously viewed planar patch. The algorithm is based on minimising the sum of square...
EUROPAR
2003
Springer
14 years 1 months ago
2003
Springer
Abstract. This paper shows how a sparse hypermatrix Cholesky factorization can be improved. This is accomplished by means of efficient codes which operate on very small dense matri...