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Showing results for M. ruyssen[Author]
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Low-Rank Plus Sparse Decomposition of Covariance Matrices Using Neural Network Parametrization.
Baes M, Herrera C, Neufeld A, Ruyssen P. Baes M, et al. Among authors: ruyssen p. IEEE Trans Neural Netw Learn Syst. 2023 Jan;34(1):171-185. doi: 10.1109/TNNLS.2021.3091598. Epub 2023 Jan 5. IEEE Trans Neural Netw Learn Syst. 2023. PMID: 34232894
Our approach consists in representing the low-rank part of the solution as the product MM(T) , where M is a rectangular matrix of appropriate size, parametrized by the coefficients of a deep neural network. ...
Our approach consists in representing the low-rank part of the solution as the product MM(T) , where M is a rectangular matrix of app …