ICIP
2007
IEEE
13 years 11 months ago
2007
IEEE
We propose a framework for exploiting dimension-reducing random projections in detection and classification problems. Our approach is based on the generalized likelihood ratio te...
ICIP
2008
IEEE
13 years 11 months ago
2008
IEEE
Compressed sensing(CS) suggests that a signal, sparse in some basis, can be recovered from a small number of random projections. In this paper, we apply the CS theory on sparse ba...
ICASSP
2008
IEEE
13 years 11 months ago
2008
IEEE
The theory of compressed sensing shows that samples in the form of random projections are optimal for recovering sparse signals in high-dimensional spaces (i.e., finding needles ...
ICANN
2009
Springer
13 years 11 months ago
2009
Springer
Backpropagation of errors is not only hard to justify from biological perspective but also it fails to solve problems requiring complex logic. A simpler algorithm based on generati...
DCC
2008
IEEE
14 years 4 months ago
2008
IEEE
A method is proposed for the compression of hyperspectral signature vectors on severely resourceconstrained encoding platforms. The proposed technique, compressive-projection prin...
KDD
2003
ACM
14 years 5 months ago
2003
ACM
Dimensionality reduction via Random Projections has attracted considerable attention in recent years. The approach has interesting theoretical underpinnings and offers computation...
KDD
2006
ACM
14 years 5 months ago
2006
ACM
There has been considerable interest in random projections, an approximate algorithm for estimating distances between pairs of points in a high-dimensional vector space. Let A Rn...