0427991 20240111140847.120140819235959.9 000343655306161 10.1109/ICASSP.2014.6854910 5 s. C cav_un_epca*0427988978-1-4799-2892-76766-6770PiscatawayIEEE2014 tensor decomposition Tucker decomposition compression cav_un_auth*0274170 Phan A. H. JP cav_un_auth*0274171 Cichocki A. JP cav_un_auth*0101212 Tichavský Petr Stochastická informatika Department of Stochastic Informatics SI SI UTIA-B Department of Stochastic Informatics Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2014/SI/tichavsky-0427991.pdf 298 kB GA14-13713S GA ČR CZ cav_un_auth*0303443 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(I^3R), which is cheaper than O(I^3R + IR^4 + R^6) of HOOI for multilinear rank-(R, R,R) tensors of size I × I × I. cav_un_auth*0305396 IEEE International Conference on Acoustics, Speech, and Signal Processing 2014 (ICASSP2014) Florence 04.05.2014-09.05.2014 IT 2015 BB 3 PO RVO:67985556 http://hdl.handle.net/11104/0235486 cav_un_auth*0303002 RIKEN JP S 2014 000343655306161 WOS 298 kB cav_un_epca*0427988 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 978-1-4799-2892-7 6766 6770 Piscataway IEEE 2014 IEEE Catalog Number: CFP14ICA-USB