Michael K. Ng

TL;DR: The results of missing/noisy color image pixels as a robust quaternion matrix completion problem are given to show that the performance of the proposed approach is better than that of the testing methods, including image inpainting methods, the tensor‐based completion method, and the quaternions completion method using semidefinite programming.

TL;DR: The experimental results on synthetic and real-world data sets are reported to illustrate the effectiveness of the proposed method that can capture strong or weak relations among feature spaces, and enhance the learning performance of heterogeneous transfer learning.

TL;DR: An efficient algorithm is designed to solve SLRM model based on alternating direction method of multipliers and thus it can efficiently deal with large-scale datasets and obtain promising and better label prediction results than state-of-the-art methods.

TL;DR: This work considers the iterative solution of weighted Toeplitz least squares problems using a variant of constraint preconditioning, and the Hermitian/skew-Hermitian splitting (HSS) preconditionser, based on an augmented system formulation.

TL;DR: Five frequently applied techniques for generating molecular data, which are micro array, RNA sequencing, quantitative polymerase chain reaction, NanoString and tissue microarray, are introduced and standardized methods should be established to help identify intrinsic subgroup signatures and build robust classifiers that pave the way toward stratified treatment of cancer patients.