Results 21 to 30 of about 3,165,100 (264)
Differentially Private Ordinary Least Squares
The Journal of Privacy and Confidentiality, 2019 Linear regression is one of the most prevalent techniques in machine learning; however, it is also common to use linear regression for its explanatory capabilities rather than label prediction.
Or Sheffet
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Non-parametric and least squares Langley plot methods [PDF]
Atmospheric Measurement Techniques, 2016 Langley plots are used to calibrate sun radiometers primarily for the measurement of the aerosol component of the atmosphere that attenuates (scatters and absorbs) incoming direct solar radiation.
P. W. Kiedron, J. J. Michalsky
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Separations, 2018 It is necessary to determine the limit of detection when validating any analytical method. For methods with a linear response, a simple and low labor-consuming procedure is to use the linear regression parameters obtained in the calibration to estimate ...
Juan M. Sanchez
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Convergence of a Distributed Least Squares
IEEE Transactions on Automatic Control, 2021 8 pages, published in IEEE Transactions on Automatic ...
Siyu Xie, Yaqi Zhang, Lei Guo 0001
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Orthogonal least squares regression with tunable kernels [PDF]
, 2005 A novel technique is proposed to construct sparse regression models based on the orthogonal least squares method with tunable kernels. The proposed technique tunes the centre vector and diagonal covariance matrix of individual regressor by incrementally ...
Wang, X.X., Chen, S., Brown, D.J.
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Total Least Squares Registration of 3D Surfaces [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013 Co-registration of point clouds of partially scanned objects is the first step of the 3D modeling workflow. The aim of coregistration is to merge the overlapping point clouds by estimating the spatial transformation parameters.
U. Aydar +3 more
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High-performance numerical algorithms and software for structured total least squares [PDF]
, 2005 We present a software package for structured total least squares approximation problems. The allowed structures in the data matrix are block-Toeplitz, block-Hankel, unstructured, and exact.
Van Huffel, S. +3 more
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Teaching Least Squares in Matrix Notation
Ratio Mathematica, 2017 Material for teaching least squares at the undergraduate level in matrix notation is reported. The weighted least squares equations are first derived in matrix form; equivalence with the standard results obtained by standard algebra are then given for ...
Guglielmo Monaco, Aniello Fedullo
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The performance of unweighted least squares and regularized unweighted least squares in estimating factor loadings in structural equation modeling [PDF]
International Journal of Data and Network Science, 2023 In a confirmatory study, researchers are expected to employ the covariance-based structural equation modeling (CB-SEM). One of the key presumptions when utilizing CB-SEM is that the data is multivariate normal.
Nurul Raudhah Zulkifli +2 more
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Combinatorics of least-squares trees [PDF]
Proceedings of the National Academy of Sciences, 2008 A recurring theme in the least-squares approach to phylogenetics has been the discovery of elegant combinatorial formulas for the least-squares estimates of edge lengths. These formulas have proved useful for the development of efficient algorithms, and have also been important for understanding connections among popular phylogeny algorithms.
Mihaescu, Radu, Pachter, Lior
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