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Abstract: Covariance matrix estimation is of great importance in statistical signal processing. This paper considers covariance matrix estimation from correlated ...

Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python ...

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Data assimilation (DA) is a mathematical family of methods that allows the combination of observations and models. The model is used to fill observational gaps, and ...

The mathematics behind artificial intelligence (AI) and machine learning (ML) rely on linear algebra, calculus, probability, ...

Highly efficient subsampled eigenvalue decomposition techniques are also introduced ... it still becomes computationally and memory intensive when applied to large data 4 because it requires ...

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Last year, he performed a new song, “You Can Make It,” at the BET Awards. The prospect of a Matrix-inspired music video is certainly exciting. Lana and Lilly Wachowski’s film is still ...