Results 51 to 60 of about 1,437,192 (281)
Marginal Screening for Partial Least Squares Regression
IEEE Access, 2017 Partial least squares (PLS) regression is a versatile modeling approach for high-dimensional data analysis. Recently, PLS-based variable selection has attracted great attention due to high-throughput data reduction and modeling interpretability.
Naifei Zhao, Qingsong Xu, Hong Wang
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New Developments in Sparse PLS Regression
Frontiers in Applied Mathematics and Statistics, 2021 Methods based on partial least squares (PLS) regression, which has recently gained much attention in the analysis of high-dimensional genomic datasets, have been developed since the early 2000s for performing variable selection.
Jérémy Magnanensi +6 more
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Alternating least squares as moving subspace correction
, 2018 In this note we take a new look at the local convergence of alternating optimization methods for low-rank matrices and tensors. Our abstract interpretation as sequential optimization on moving subspaces yields insightful reformulations of some known ...
Oseledets, Ivan +2 more
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Molecular Oncology, EarlyView.Pharmacologic ascorbate (vitamin C) increases ROS, disrupts cellular metabolism, and induces DNA damage in CRPC cells. These effects sensitize tumors to PARP inhibition, producing synergistic growth suppression with olaparib in vitro and significantly delayed tumor progression in vivo. Pyruvate rescue confirms ROS‐dependent activity.
Nicolas Gordon +13 more
wiley +1 more source
LEAST SQUARES MULTI-WINDOW EVOLUTIONARY SPECTRAL ESTIMATION
Electrica, 2003 We present a multi-window method for obtaining the time-frequency spectrum of non-stationary signals such as speech and music. This method is based on optimal combination of evolutionary spectra that are calculated by using multi-window Gabor expansion ...
Mahmut YALÇIN, Aydın AKAN
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A novel interpretation of least squares solution
International Journal of Mathematics and Mathematical Sciences, 1992 We show that the well-known least squares (LS) solution of an overdetermined system of linear equations is a convex combination of all the non-trivial solutions weighed by the squares of the corresponding denominator determinants of the Cramer's rule ...
Jack-Kang Chan
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Least Squares Consensus for Matching Local Features
Information, 2019 This paper presents a new approach to estimate the consensus in a data set. Under the framework of RANSAC, the perturbation on data has not been considered sufficiently.
Qingming Zhang, Buhai Shi, Haibo Xu
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Local Regularization Assisted Orthogonal Least Squares Regression
, 2006 A locally regularized orthogonal least squares (LROLS) algorithm is proposed for constructing parsimonious or sparse regression models that generalize well.
Chen, S.
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Plecstatin inhibits hepatocellular carcinoma tumorigenesis and invasion through cytolinker plectin
Molecular Oncology, EarlyView.The ruthenium‐based metallodrug plecstatin exerts its anticancer effect in hepatocellular carcinoma (HCC) primarily through selective targeting of plectin. By disrupting plectin‐mediated cytoskeletal organization, plecstatin inhibits anchorage‐dependent growth, cell polarization, and tumor cell dissemination.
Zuzana Outla +10 more
wiley +1 more source
Implicitly Constrained Semi-Supervised Least Squares Classification
, 2015 We introduce a novel semi-supervised version of the least squares classifier. This implicitly constrained least squares (ICLS) classifier minimizes the squared loss on the labeled data among the set of parameters implied by all possible labelings of the ...
B Widrow +16 more
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