rBDLR is an unsupervised representation learning method that combines Frobenius-norm low-rank coding, robust clean-space recovery, adaptive locality weighting, and block-diagonal regularization to improve image recognition and clustering.
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Robust Subspace Discovery by Block-diagonal Adaptive Locality-constrained Representation
rBDLR is an unsupervised representation learning method that combines Frobenius-norm low-rank coding, robust clean-space recovery, adaptive locality weighting, and block-diagonal regularization to improve image recognition and clustering.