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SIAMMAX
2010
134views more  SIAMMAX 2010»
12 years 11 months ago
Dynamical Tensor Approximation
For the approximation of time-dependent data tensors and of solutions to tensor differential equations by tensors of low Tucker rank, we study a computational approach that can be ...
Othmar Koch, Christian Lubich
MCS
2008
Springer
13 years 4 months ago
Dynamical low-rank approximation: applications and numerical experiments
Dynamical low-rank approximation is a differential-equation based approach to efficiently computing low-rank approximations to time-dependent large data matrices or to solutions o...
Achim Nonnenmacher, Christian Lubich
ICIP
2007
IEEE
14 years 6 months ago
Hierarchical Tensor Approximation of Multidimensional Images
Visual data comprises of multi-scale and inhomogeneous signals. In this paper, we exploit these characteristics and develop an adaptive data approximation technique based on a hie...
Qing Wu, Tian Xia, Yizhou Yu
ICA
2012
Springer
12 years 10 days ago
On Revealing Replicating Structures in Multiway Data: A Novel Tensor Decomposition Approach
A novel tensor decomposition called pattern or P-decomposition is proposed to make it possible to identify replicating structures in complex data, such as textures and patterns in ...
Anh Huy Phan, Andrzej Cichocki, Petr Tichavsk&yacu...
TVCG
2008
136views more  TVCG 2008»
13 years 4 months ago
Hierarchical Tensor Approximation of Multi-Dimensional Visual Data
Abstract-- Visual data comprise of multi-scale and inhomogeneous signals. In this paper, we exploit these characteristics and develop a compact data representation technique based ...
Qing Wu, Tian Xia, Chun Chen, Hsueh-Yi Sean Lin, H...