ON FAST ALGORITHMS FOR ORTHOGONAL TUCKER DECOMPOSITION

被引：0
|
作者：
Anh-Huy Phan [1 ]
Cichocki, Andrzej [1 ]
Tichavsky, Petr [2 ]
机构：
[1] RIKEN, Brain Sci Inst, Wako, Japan
[2] Acad Sci Czech Republ, Inst Informat Theory & Automat, CR-18208 Prague, Czech Republic
来源：
2014 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2014年
关键词：
tensor decomposition; Tucker decomposition; orthogonality constraint; Cayley transform; Crank-Nicholson-like scheme; APPROXIMATION;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
We propose algorithms for Tucker tensor decomposition, which can avoid computing singular value decomposition or eigenvalue decomposition of large matrices as in the work-horse higher order orthogonal iteration (HOOI) algorithm. The novel algorithms require computational cost of O((IR)-R-3), which is cheaper than O((IR)-R-3 + IR4 + R-6) of HOOI for multilinear rank-(R, R, R) tensors of size I x I x I.
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页数：5
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