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PRL
2006
117views more  PRL 2006»
13 years 3 months ago
Non-iterative generalized low rank approximation of matrices
: As an extension to 2DPCA, Generalized Low Rank Approximation of Matrices (GLRAM) applies two-sided (i.e., the left and right) rather than single-sided (i.e., the left or the righ...
Jun Liu, Songcan Chen
SDM
2007
SIAM
96views Data Mining» more  SDM 2007»
13 years 5 months ago
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 recentl...
Bernard N. Sheehan, Yousef Saad
SDM
2010
SIAM
153views Data Mining» more  SDM 2010»
13 years 5 months ago
Reconstruction from Randomized Graph via Low Rank Approximation
The privacy concerns associated with data analysis over social networks have spurred recent research on privacypreserving social network analysis, particularly on privacypreservin...
Leting Wu, Xiaowei Ying, Xintao Wu
RT
2005
Springer
13 years 9 months ago
Online Construction of Surface Light Fields
We present a system for interactively capturing, constructing, and rendering surface light fields by incrementally building a low rank approximation to the surface light field. ...
Greg Coombe, Chad Hantak, Anselmo Lastra, Radek Gr...
STOC
2001
ACM
138views Algorithms» more  STOC 2001»
14 years 3 months ago
Fast computation of low rank matrix
Given a matrix A, it is often desirable to find a good approximation to A that has low rank. We introduce a simple technique for accelerating the computation of such approximation...
Dimitris Achlioptas, Frank McSherry