36 search results - page 6 / 8 » Connecting spectral and spring methods for manifold learning |
103
click to vote
NIPS
2001
14 years 11 months ago
2001
High dimensional data that lies on or near a low dimensional manifold can be described by a collection of local linear models. Such a description, however, does not provide a glob...
141
click to vote
ICML
2003
IEEE
15 years 10 months ago
2003
IEEE
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
ECML
2005
Springer
15 years 3 months ago
2005
Springer
Spectral methods for embedding graphs and immersing data manifolds in low-dimensional speaces are notoriously unstable due to insufficient and/or numberically ill-conditioned con...
121
Voted
CVPR
2011
IEEE
14 years 5 months ago
2011
IEEE
This paper addresses the problem of learning similaritypreserving binary codes for efficient retrieval in large-scale image collections. We propose a simple and efficient altern...
102
click to vote
ML
2010
ACM
14 years 4 months ago
2010
ACM
Spectral analysis approaches have been actively studied in machine learning and data mining areas, due to their generality, efficiency, and rich theoretical foundations. As a natur...