This book focuses on Least Squares Support Vector Machines (LS-SVMs) which are reformulations to standard SVMs. LS-SVMs are closely related to regularization networks and Gaussian processes but additionally emphasize and exploit primal-dual interpret

block-matching 3D filtering (BM3D) [2], and low-rank regularization [3], single-image based denoising performance has greatly improved, with image details well recovered when the image is slightly noisy. However, with the increase of noise le