335 search results - page 4 / 67 » Neighborly Embedded Manifolds |
ICPR
2010
IEEE
14 years 4 days ago
2010
IEEE
—The problem we address in the paper is how to learn a joint representation from data lying on multiple manifolds. We are given multiple data sets and there is an underlying comm...
NIPS
2003
13 years 10 months ago
2003
Spectral methods for nonlinear dimensionality reduction (NLDR) impose a neighborhood graph on point data and compute eigenfunctions of a quadratic form generated from the graph. W...
ICML
2007
IEEE
14 years 9 months ago
2007
IEEE
In this work we take a novel view of nonlinear manifold learning. Usually, manifold learning is formulated in terms of finding an embedding or `unrolling' of a manifold into ...
ECCV
2010
Springer
14 years 1 months ago
2010
Springer
Approximate Nearest Neighbor (ANN) methods such as Locality Sensitive Hashing, Semantic Hashing, and Spectral Hashing, provide computationally ecient procedures for nding objects...
CVPR
2009
IEEE
14 years 3 months ago
2009
IEEE
This paper presents a novel discriminative learning method, called Manifold Discriminant Analysis (MDA), to solve the problem of image set classification. By modeling each image s...