Robust Low-rank subspace segmentation with finite mixture noise
Pattern Recognition, pp. 55-67, 2019.
Abstract Subspace segmentation or clustering remains a challenge of interest in computer vision when handling complex noise existing in high-dimensional data. Most of the current sparse representation or minimum-rank based techniques are constructed on l 1 -norm or l 2 -norm losses, which is sensitive to outliers. Finite mixture model, ...More
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