Graph Embedding and Extensions: A General Framework for Dimensionality Reduction
Published in IEEE Transactions on Pattern Analysis and Machine Intelligence • Dec 1, 2006
NobleIDNI6P04W45R54S09
Authors:,,
Shuicheng Yan
Dong Xu
Benyu Zhang
Abstract
A large family of algorithms - supervised or unsupervised; stemming from statistics or geometry theory - has been designed to provide different solutions to the problem of dimensionality reduction. Despite the different motivations of these algorithms, we present in this paper a general formulation ...
Finding related papers...
Discussions
(0)No comments yet
Be the first to share your thoughts!