论文阅读——Efficient and Robust Feature Selection via Joint L2,1-Norms Minimization
1、前言 最近由于对结构化多任务学习，以及对带范数目标函数求解的学习，一直都很想求解带L2,1范数的目标函数（其实这只是个过程），针对这样的不光滑目标函数，梯度降低法并不合适。web 虽然sklearn中的MultiTaskLasso也是这样的目标函数，而且使用了坐标降低法来求解，可是当目标函数中的损失函数也用L2,1范数时我又懵圈了。算法 正当我琢磨是否是能把两部分合在一块儿求解一个L2,1范数
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