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2007
IEEE

Non-negative Tensor Factorization Based on Alternating Large-scale Non-negativity-constrained Least Squares

11 years 5 months ago
Non-negative Tensor Factorization Based on Alternating Large-scale Non-negativity-constrained Least Squares
Non-negative matrix factorization (NMF) and non-negative tensor factorization (NTF) have attracted much attention and have been successfully applied to numerous data analysis problems where the components of the data are necessarily non-negative such as chemical concentrations in experimental results or pixels in digital images. Especially, Andersson and Bro's PARAFAC algorithm with nonnegativity constraints (AB-PARAFAC-NC) provided the stateof-the-art NTF algorithm, which uses Bro and de Jong's nonnegativity-constrained least squares with single right hand side (NLS/S-RHS). However, solving an NLS with multiple right hand sides (NLS/M-RHS) problem by multiple NLS/SRHS problems is not recommended due to hidden redundant computation. In this paper, we propose an NTF algorithm based on alternating large-scale non-negativity-constrained least squares (NTF/ANLS) using NLS/M-RHS. In addition, we introduce an algorithm for the regularized NTF based on ANLS (RNTF/ANLS). Our experime...
Hyunsoo Kim, Haesun Park, Lars Eldén
Added 12 Aug 2010
Updated 12 Aug 2010
Type Conference
Year 2007
Where BIBE
Authors Hyunsoo Kim, Haesun Park, Lars Eldén
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