On Low Rank Approximation Of 3-Tensors Based On Regularized t-SVD

摘要

In recent applications, regularization becomes an increasing trend. Regularized SVD has been studied by many leading experts in machine learning. Recently, Misha E. Kilmer and Carla D. Martin introduced t-SVD of 3-tensors, which has many advantages than old definitions of tensor SVD. In this paper, we present a regularized t-SVD (Rt-SVD) for 3tensors, present a regularized t-SVD (Rt-SVD) and an efficient computational algorithm.