Rank Splitting for CANDECOMP/PARAFAC

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F15%3A00447197" target="_blank" >RIV/67985556:_____/15:00447197 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-22482-4_4" target="_blank" >http://dx.doi.org/10.1007/978-3-319-22482-4_4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-22482-4_4" target="_blank" >10.1007/978-3-319-22482-4_4</a>

Result language
angličtina
Original language name
Rank Splitting for CANDECOMP/PARAFAC
Original language description
CANDECOMP/PARAFAC (CP) approximates multiway data by a sum of rank-1 tensors. Our recent study has presented a method to rank-1 tensor deflation, i.e. sequential extraction of rank-1 tensor components. In this paper, we extend the method to block deflation problem. When at least two factor matrices have full column rank, one can extract two rank-1 tensors simultaneously, and rank of the data tensor is reduced by 2. For decomposition of order-3 tensors of size RRR and rank-R, the block deflation has a complexity of O(R^3) per iteration which is lower than the cost O(R^4) of the ALS algorithm for the overall CP decomposition.
Czech name
—
Czech description
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Project
<a href="/en/project/GA14-13713S" target="_blank" >GA14-13713S: Tensor Decomposition Methods and Their Applications</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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