Think globally, fit locally: unsupervised learning of low dimensional manifolds
The Journal of Machine Learning Research
Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment
SIAM Journal on Scientific Computing
Feature extraction by learning Lorentzian metric tensor and its extensions
Pattern Recognition
Locally linear embedding: a survey
Artificial Intelligence Review
Lorentzian discriminant projection and its applications
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
Hi-index | 0.02 |
LLE is a well-known method to nonlinear dimensionality reduction. In this short paper, we present an alternative way to formulate LLE. The alignment technique is exploited to align the local coordinates on the local patches of manifolds to be the global ones. The efficient computation of embedding coordinates of LLE automatically appears in the proposed framework.