Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction

We propose a unified manifold learning framework for semi-supervised and unsupervised dimension reduction by employing a simple but effective linear regression function to map the new data points. For semi-supervised dimension reduction, we aim to find the optimal prediction labels F for all the tra...

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