Higher Order Orthogonal Iteration of Tensors (HOOI) and its Relation to PCA and GLRAM

This paper presents a unified view of a number of dimension reduction techniques under the common framework of tensors. Specifically, it is established that PCA, and the recently introduced 2-D PCA and Generalized Low Rank Approximation of Matrices (GLRAM), are special instances of the higher order orthogonal iteration of tensors (HOOI). The connection of these algorithms to HOOI has not been pointed out before in the literature. The pros and cons of these specializations versus HOOI are discussed.

• Type: Conference
• Year: 2007
• Where: SDM
• Authors: Bernard N. Sheehan, Yousef Saad
• Keywords: Data Mining, Dimension Reduction Techniques, Low Rank Approximation, Order Orthogonal Iteration, SDM 2007