アルゴリズム:Algorithms Protected: Theory of Noisy L1-Norm Minimization as Machine Learning Based on Sparsity (2)
Theory of noisy L1 norm minimization as machine learning based on sparsity for digital transformation, artificial intelligence, and machine learning tasks numerical examples, heat maps, artificial data, restricted strongly convex, restricted isometric, k-sparse vector, norm independence, subdifferentiation, convex function, regression coefficient vector, orthogonal complementary space