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- W1660201478 abstract "In this paper we address the problem of estimating the interaction matrices of Paralind decomposition. In general, this is an ill-posed problem admitting an infinite number of solutions. First we study the gain of imposing sparsity constraints on the interaction matrices, in terms of model identifiability. Then, we propose a new algorithm (S-Paralind) for fitting the Paralind model, using a l 2 — l 1 optimization step for estimating the interaction matrix. This new approach provides more accurate and robust estimates of the constraint matrices than ALS-Paralind, thus improving the interpretabil-ity of the Paralind decomposition." @default.
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- W1660201478 date "2012-08-27" @default.
- W1660201478 modified "2023-09-27" @default.
- W1660201478 title "A blind sparse approach for estimating constraint matrices in Paralind data models" @default.
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