Learning With $\ell ^{1}$-Graph for Image Analysis

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How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Sparse representation or collaborative representation: Which helps face recognition? (2011, background): “Cheng et al. [11] discussed the l 1 -graph for classification, and Yang et al. [12] combined sparse coding with linear spatial pyramid matching for image classification.”
Non-negative low rank and sparse graph for semi-supervised learning (2012, methodology): “We combine different graphs with these two SSL frameworks, and quantitatively evaluate their performance by following the approaches in [20, 7, 18, 8].”
View-invariant human action recognition via robust locally adaptive multi-view learning (2015, methodology): “(7), we use the r power of α i instead of α i (Cheng et al., 2010).”