@inproceedings{58155b8b3d1e493b91a216ae84660ffa,
title = "Higher order orthogonal iteration of tensors (HOOT) and its relation to PCA and GLRAM",
abstract = "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 (HOOT). The connection of these algorithms to HOOT has not been pointed out before in the literature. The pros and cons of these specializations versus HOOT are discussed.",
keywords = "Dimension reduction, GLRAM, HOOT, HOSVD, Principal component analysis, Tensor",
author = "Sheehan, {Bernard N.} and Yousef Saad",
year = "2007",
language = "English (US)",
isbn = "9780898716306",
series = "Proceedings of the 7th SIAM International Conference on Data Mining",
pages = "355--365",
booktitle = "Proceedings of the 7th SIAM International Conference on Data Mining",
note = "7th SIAM International Conference on Data Mining ; Conference date: 26-04-2007 Through 28-04-2007",
}