Latest least squares regression (LSR) methods aim to learn slack regression targets to replace strict zero-one labels. However, the difference between intra-class targets can also be highlighted when enhancing the distance between different classes, and roughly persuing relaxed targets may lead to the problem of overfitting. To solve above problems, we propose a low-rank discriminative least squares regression model (LRDLSR) for multi-class image classification. Specifically, LRDLSR class-wisely imposes low-r…
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