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second-order optimization based adaptive parafac decomposition of three-way tensors开题资料.pdf


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second-order optimization based adaptive parafac decomposition of three-way tensors开题资料.pdf
文档介绍:
Digital Signal Processing 63 (2017) 100–111
Contents lists available at ScienceDirect
Digital Signal Processing
www.elsevier.com/locate/dsp
Second-order optimization based adaptive PARAFAC decomposition of
three-way tensors

Viet-Dung Nguyen a, , Karim Abed-Meraim a, Nguyen Linh-Trung b
a PRISME Laboratory, University of Orléans, 12 rue de Blois BP 6744, Orléans, France
b University of Engineering and Technology, Vietnam National University, Hanoi, 144 Xuan Thuy, Cau Giay, Hanoi, Viet Nam
a r t i c l e i n f o a b s t r a c t
Article history: A fast adaptive parallel factor (PARAFAC) decomposition algorithm is proposed for a class of third-
Available online 9 January 2017 order tensors that have one dimension growing linearly with time. It is based on an alternating least
squares approach in conjunction with a Newton-type optimization technique. By preserving the Khatri–
Keywords:
Rao product and exploiting the reduced-rank update structure of the estimated subspace at each time
Fast adaptive PARAFAC
instant, the algorithm achieves linear complexity and superior convergence performance. A modified
Big data
Parallel computing version of the algorithm is also proposed to deal with the non-negative constraint. In addition, parallel
Non-negative constraint implementation issues are investigated. Finally, the performance of the algorithm is numerically studied
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