Title :
Dimensionality Reduction via Subspace and Submanifold Learning [From the Guest Editors]
Author :
Yi Ma ; Niyogi, P. ; Sapiro, Guillermo ; Vidal, Rene
fDate :
3/1/2011 12:00:00 AM
Abstract :
The featured articles cover very representative models and techniques that people have developed in recent years for modeling and extracting low-dimension al structures of high-dimensional data.
Keywords :
data handling; learning (artificial intelligence); dimensionality reduction; high-dimensional data; submanifold learning; subspace learning; Audio databases; Information analysis; Learning systems; Search problems; Special issues and sections; Web services;
Journal_Title :
Signal Processing Magazine, IEEE
DOI :
10.1109/MSP.2010.940005
