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Dimensionality Reduction via Subspace and Submanifold Learning [From the Guest Editors]

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4 Author(s)

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.

Published in:

Signal Processing Magazine, IEEE  (Volume:28 ,  Issue: 2 )