Results 131 to 140 of about 9,171,861 (296)
Algorithms for lp Low Rank Approximation [PDF]
, 2017 We consider the problem of approximating a given matrix by a low-rank matrix so as to minimize the entry-wise lp-approximation error, for any P ≥ 1; the case p = 2 is the classical SVD problem.
Kumar, Ravi +5 more
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Approximate low-rank factorization with structured factors
, 2010 An approximate rank revealing factorization problem with structure constraints on the normalized factors is considered. Examples of structure, motivated by an application in microarray data analysis, are sparsity, nonnegativity, periodicity, and ...
Niranjan, Mahesan, Markovsky, Ivan
core +1 more source
Randomized SVD Methods in Hyperspectral Imaging
Journal of Electrical and Computer Engineering, 2012 We present a randomized singular value decomposition (rSVD) method for the purposes of lossless compression, reconstruction, classification, and target detection with hyperspectral (HSI) data.
Jiani Zhang +4 more
doaj +1 more source
FEBS Letters, EarlyView.This review focuses on the role of autophagy and mitophagy in maintaining pancreatic β‐cell function and homeostasis. We discuss how genetic defects affecting these pathways contribute to the development of type 1, type 2, monogenic, and gestational diabetes. We further explore their potential as therapeutic targets. Created in BioRender.
Yunkyeong Lee +2 more
wiley +1 more source
On the geometric interpretation of the nonnegative rank [PDF]
The nonnegative rank of a nonnegative matrix is the minimum number of nonnegative rank-one factors needed to reconstruct it exactly. The problem of determining this rank and computing the corresponding nonnegative factors is difficult; however it has ...
GILLIS, Nicolas, GLINEUR, François
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FEBS Letters, EarlyView.Obesity raises blood levels of PAI‐1, a protein linked to metabolic dysfunction‐associated steatotic liver disease in people with obesity. In female mice fed a high‐fat diet, partially lowering PAI‐1 led to smaller subcutaneous fat cells and lower liver cholesterol, without changing body weight or insulin sensitivity.
Claudia E. Ramirez Bustamante +10 more
wiley +1 more source
Dynamical low-rank approximation
, 2006 . For the low rank approximation of time-dependent data matrices and of solutions to matrix differential equations, an increment-based computational approach is proposed and analyzed.
Christian Lubich, Othmar Koch
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IEEE AccessTo excel at their domain, large language models are comprised of billions of parameters. Yet, this comes at the cost of huge memory requirements, restricting their applicability in resource-constrained environments.
Athanasios Ntovas +3 more
doaj +1 more source
Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry
FEBS Letters, EarlyView.EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri +5 more
wiley +1 more source
Rank reduction of correlation matrices by majorization [PDF]
In this paper a novel method is developed for the problem of finding a low-rank correlation matrix nearest to a given correlation matrix. The method is based on majorization and therefore it is globally convergent. The method is computationally efficient,
Groenen, P.J.F., Pietersz, R.
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