141 search results - page 21 / 29 » Grouping and dimensionality reduction by locally linear embe... |
PAKDD
2005
ACM
14 years 2 months ago
2005
ACM
We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separatel...
DATE
2006
IEEE
14 years 3 months ago
2006
IEEE
In many computer systems with large data computations, the delay of memory access is one of the major performance bottlenecks. In this paper, we propose an enhanced field remappi...
NIPS
2004
13 years 10 months ago
2004
In this paper we propose a novel method for learning a Mahalanobis distance measure to be used in the KNN classification algorithm. The algorithm directly maximizes a stochastic v...
ICPR
2002
IEEE
14 years 10 months ago
2002
IEEE
Manifold Pursuit (MP) extends Principal Component Analysis to be invariant to a desired group of image-plane transformations of an ensemble of un-aligned images. We derive a simpl...
ICML
2005
IEEE
14 years 9 months ago
2005
IEEE
Recently, several manifold learning algorithms have been proposed, such as ISOMAP (Tenenbaum et al., 2000), Locally Linear Embedding (Roweis & Saul, 2000), Laplacian Eigenmap ...