Fast algorithms for non-convex tensor completion problems Fast algorithms for non-convex tensor completion problems

Multi-dimensional image processing plays a pivotal role in diverse fields such as medicine, research, graphics, industry, remote sensing, virtual reality, and geospatial mapping, enabling advanced visualization and analysis. Traditional methods for processing multi-dimensional data, such as matrix-b...

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Vydáno v:	Afrika mathematica Ročník 36; číslo 2; s. 65
Hlavní autoři:	Kanwal, Asia, ur Rahman, Mati, Boulaaras, Salah
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2025 Springer Nature B.V
Témata:	Accuracy Algorithms Applications of Mathematics Approximation Complexity Convex analysis Convexity Data recovery Datasets Decomposition Fourier transforms Gray scale History of Mathematical Sciences Hyperspectral imaging Image processing Machine learning Mathematics Mathematics and Statistics Mathematics Education Multidimensional data Multidimensional methods Optimization Optimization techniques Remote sensing Singular value decomposition Tensors Video Virtual reality 68U10 68W40 Randomized singular value decomposition (r-SVD) Multi-dimensional image processing Tensor singular value decomposition (t-SVD) 42B10 Surrogate functions Alternating direction method of multipliers (ADMM)
ISSN:	1012-9405, 2190-7668
On-line přístup:	Získat plný text
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