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Keywords: singular value decomposition
Journal Article
Distinguishing the transitions of fluorescence spectra of tryptophan-134 and 213 in BSA induced by bindings of UV filters, oxybenzone-3, and avobenzone Get access
Bulletin of the Chemical Society of Japan, Volume 97, Issue 6, June 2024, uoae058, https://doi.org/10.1093/bulcsj/uoae058
Published: 03 June 2024
..., diclofenac, and ibuprofen bond with BSA was investigated as the influence on the inherent fluorescence of BSA by the interaction of these compounds with BSA using fluorescence measurement and singular value decomposition (SVD). SVD results facilitated the adsorption analysis of these compounds and BSA...
Journal Article
SGCLDGA: unveiling drug–gene associations through simple graph contrastive learning
Briefings in Bioinformatics, Volume 25, Issue 3, May 2024, bbae231, https://doi.org/10.1093/bib/bbae231
Published: 16 May 2024
... learning to predict unknown drug–gene associations. SGCLDGA employs GCNs to extract vector representations of drugs and genes from the original bipartite graph. Subsequently, singular value decomposition (SVD) is employed to enhance the graph and generate multiple views. The model performs contrastive...
Journal Article
Frequency-weighted and frequency interval Gramian framework-based model reduction using singular value decomposition Get access
IMA Journal of Mathematical Control and Information, Volume 41, Issue 1, March 2024, Pages 57–72, https://doi.org/10.1093/imamci/dnad036
Published: 17 February 2024
... interval singular value decomposition Model order reduction (MOR) is a significantly used tool for contemporary control system analysis and design. A reduced-order model (ROM) obtained via MOR should exhibit characteristics similar to the existing system while minimizing some form of error between...
Journal Article
Inexact augmented Lagrangian method-based full-waveform inversion with randomized singular value decomposition
Journal of Geophysics and Engineering, Volume 21, Issue 2, April 2024, Pages 572–597, https://doi.org/10.1093/jge/gxae015
Published: 31 January 2024
... complex conditions caused by random noise contamination, initial model dependence, or the selection of parameters to be estimated. Our algorithm considers an effective image processing and dimension reduction tool, randomized singular value decomposition-weighted truncated nuclear norm regularization...
Journal Article
LDA-VGHB: identifying potential lncRNA–disease associations with singular value decomposition, variational graph auto-encoder and heterogeneous Newton boosting machine
Briefings in Bioinformatics, Volume 25, Issue 1, January 2024, bbad466, https://doi.org/10.1093/bib/bbad466
Published: 20 December 2023
... that LDA-VGHB was capable of identifying possible lncRNAs for complex diseases. LDA-VGHB is publicly available at https://github.com/plhhnu/LDA-VGHB . lncRNA–disease association singular value decomposition variational graph autoencoder heterogeneous Newton boosting machine National Natural Science...
Journal Article
Which airways should we treat? Structure–function relationships and estimation of the singular input modes from the forward model alone Get access
Mathematical Medicine and Biology: A Journal of the IMA, Volume 40, Issue 4, December 2023, Pages 291–307, https://doi.org/10.1093/imammb/dqad006
Published: 29 September 2023
... Structure–function relationships occur throughout the sciences. Motivated by optimization of such systems, we develop a framework for estimating the input modes from the singular value decomposition from the action of the forward operator alone. These can then be used to determine the input (structure...
Journal Article
High-precision magnetization vector inversion: application to magnetic data in the presence of significant remanent magnetization
Journal of Geophysics and Engineering, Volume 19, Issue 6, December 2022, Pages 1308–1319, https://doi.org/10.1093/jge/gxac085
Published: 28 November 2022
..., the L1-norm is modified and introduced into the inversion algorithm to obtain compact results. Furthermore, to reduce the computational cost, a randomized singular value decomposition is used to replace the traditional singular value decomposition and iteratively minimize the proposed objective function...
Journal Article
Mixed precision low-rank approximations and their application to block low-rank LU factorization Get access
IMA Journal of Numerical Analysis, Volume 43, Issue 4, July 2023, Pages 2198–2227, https://doi.org/10.1093/imanum/drac037
Published: 23 August 2022
... linear algebra rounding error analysis floating-point arithmetic mixed precision algorithms multiprecision algorithms block low-rank matrices data sparse matrices LU factorization linear systems low-rank approximations singular value decomposition The emergence of low precision arithmetics...
Journal Article
ImposeSVD: Incrementing PureSVD For Top-N Recommendations for Cold-Start Problems and Sparse Datasets Get access
The Computer Journal, Volume 66, Issue 11, November 2023, Pages 2595–2622, https://doi.org/10.1093/comjnl/bxac106
Published: 02 August 2022
...Hakan Yilmazer; Selma Ayşe Özel In our models : To overcome these challenges, the CBF or CF methods have been applied to the recommendations in sparse datasets in various studies [ 9 ]. The application of CF method has shown successful results with singular value decomposition (SVD) [ 14 ], which...
Journal Article
Photoinduced isomerization sampling of retinal in bacteriorhodopsin
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PNAS Nexus
PNAS Nexus, Volume 1, Issue 3, July 2022, pgac103, https://doi.org/10.1093/pnasnexus/pgac103
Published: 01 July 2022
... chromophore yet governed by stereoselectivity of its protein pocket. The method of a numerical resolution of concurrent events from mixed observations is also generally applicable. charge separation proton pump serial crystallography singular value decomposition X-ray free electron laser National...
Journal Article
Removing the Influence of Group Variables in High-Dimensional Predictive Modelling
Journal of the Royal Statistical Society Series A: Statistics in Society, Volume 184, Issue 3, July 2021, Pages 791–811, https://doi.org/10.1111/rssa.12613
Published: 15 April 2021
... different in the two applications illustrates the broad applicability of our approach. batch effects constrained optimization criminal justice neuroscience orthogonal predictions predictive modelling singular value decomposition Laura & John Arnold Foundation United States National...
Journal Article
Robust Image Hashing With Singular Values Of Quaternion SVD Get access
The Computer Journal, Volume 64, Issue 11, November 2021, Pages 1656–1671, https://doi.org/10.1093/comjnl/bxz127
Published: 09 December 2019
... used singular value decomposition (SVD), CVA and Canny operator to calculate circle-based variances and block-based variances, which are quantized and scrambled to make secure hash. This algorithm has good perceptual robustness, but its running speed must be improved. Tang et al. [ 45...
Journal Article
OCMA: Fast, Memory-Efficient Factorization of Prohibitively Large Relationship Matrices
G3 Genes|Genomes|Genetics, Volume 9, Issue 1, 1 January 2019, Pages 13–19, https://doi.org/10.1534/g3.118.200908
Published: 01 January 2019
... as an alternative to eigen-decomposition is the Singular Value Decomposition (SVD) of a rectangular matrix (e.g., a genotype matrix) which avoids heavy computations but approximately achieves similar precision. For instance, in the setting of a LMM, David Heckerman’s group has developed a method...
Journal Article
A Reduced Rank Regression Model for Local Variation in Solar Radiation
Journal of the Royal Statistical Society Series C: Applied Statistics, Volume 41, Issue 2, June 1992, Pages 381–387, https://doi.org/10.2307/2347569
Published: 05 December 2018
... to the south of Edinburgh. Singular value decompositions of the data matrix of monthly means, with and without subtraction of row and/or column averages, revealed the pattern of variations. A reduced rank regression model was used, which related site weightings in the decomposition to physical characteristics...
Journal Article
Application of the Parametric Bootstrap to Models that Incorporate a Singular Value Decomposition
Journal of the Royal Statistical Society Series C: Applied Statistics, Volume 44, Issue 1, March 1995, Pages 31–49, https://doi.org/10.2307/2986193
Published: 05 December 2018
...Luis Milan; Joe Whittaker App/. Statist. (1995) 44, No.1, pp. 31 -49 Application of the Parametric Bootstrap to Models that Incorporate a Singular Value Decomposition By LUIS MILAN and JOE WHITTAKERt Lancaster University, UK [Received January 1993. Final revision December 1993] SUMMARY Simulation...
Journal Article
Maximum Likelihood Estimation of the RC(M) Association Model
Journal of the Royal Statistical Society Series C: Applied Statistics, Volume 39, Issue 1, March 1990, Pages 152–167, https://doi.org/10.2307/2347833
Published: 05 December 2018
... of the Oxford University Press, Standard Journals Publication Model ( https://dbpia.nl.go.kr/journals/pages/open_access/funder_policies/chorus/standard_publication_model ) Association models Contingency table Maximum likelihood Singular value decomposition References Becker , M. P. ( 1985...
Journal Article
Principal Components and Regression by Singular Value Decomposition on a Small Computer
Journal of the Royal Statistical Society Series C: Applied Statistics, Volume 25, Issue 3, November 1976, Pages 210–216, https://doi.org/10.2307/2347228
Published: 05 December 2018
..., Standard Journals Publication Model ( https://dbpia.nl.go.kr/journals/pages/open_access/funder_policies/chorus/standard_publication_model ) Summary A compact program for performing a variety of regression and principal component computations is described. A singular value decomposition of the data...
Journal Article
Least Squares Approximation of Matrices by Additive and Multiplicative Models
Journal of the Royal Statistical Society: Series B (Methodological), Volume 40, Issue 2, January 1978, Pages 186–196, https://doi.org/10.1111/j.2517-6161.1978.tb01663.x
Published: 05 December 2018
... applications are shown in principal component analysis, in biplot graphical display and in fitting additive or Mandel-type models to two-way tables. least squares reduced rank bilinear models singular value decomposition wishart matrix principal components biplot characteristic root statistics...
Journal Article
Reduced-Rank Regression and Canonical Analysis
Journal of the Royal Statistical Society: Series B (Methodological), Volume 43, Issue 2, January 1981, Pages 183–189, https://doi.org/10.1111/j.2517-6161.1981.tb01169.x
Published: 05 December 2018
... and Tso, 1980) and demonstrates straightforwardly the intimate connection between reduced-rank regression and canonical analysis. A geometric interpretation of the analysis is given. maximum likelihood reduced-rank regression canonical analysis matrix inequality geometry singular value decomposition...
Journal Article
Procedures for Reduced-Rank Regression
Journal of the Royal Statistical Society Series C: Applied Statistics, Volume 31, Issue 3, November 1982, Pages 244–255, https://doi.org/10.2307/2347998
Published: 05 December 2018
... procedures for the analysis of the reduced-rank regression model. A new method is proposed for parameter estimation which is justified by a leastsquares analysis employing matrix singular-value decomposition and the Eckart-Young theorem. The application of the model is illustrated by the regression analysis...
