Results 11 to 20 of about 647,667 (335)
Dimensional reduction by conformal bootstrap [PDF]
Progress of Theoretical and Experimental Physics, 2019 Abstract Dimensional reductions in the branched polymer model and the random field Ising model (RFIM) are discussed by a conformal bootstrap method. Small minors are applied for the evaluations of the scale dimensions of these two models and the results are compared to the $D'=D-2$D Yang–Lee edge singularity and to the pure $D'=D-2$D ...
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Exploring the Influence of Dimensionality Reduction on Anomaly Detection Performance in Multivariate Time Series [PDF]
IEEE AccessThis paper presents an extensive empirical study on the integration of dimensionality reduction techniques with advanced unsupervised time series anomaly detection models, focusing on the MUTANT and Anomaly-Transformer models.
Mahsun Altin, Altan Cakir
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Supersymmetry breaking by dimensional reduction over coset spaces [PDF]
Phys.Lett.B504:122-130,2001, 2001 We study the dimensional reduction of a ten-dimensional supersymmetric E_8 gauge theory over six-dimensional coset spaces. We find that the coset space dimensional reduction over a symmetric coset space leaves the four dimensional gauge theory without any track of the original supersymmetry.
P. Manousselis, George Zoupanos
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Dimensional reduction in the sky [PDF]
Physical Review D, 2013 We explore the cosmological implications of a mechanism found in several approaches to quantum-gravity, whereby the spectral dimension of spacetime runs from the standard value of 4 in the infrared (IR) to a smaller value in the ultraviolet (UV). Specifically, we invoke the picture where the phenomenon is associated with modified dispersion relations ...
João Magueijo +4 more
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Supervised dimensionality reduction for big data
Nature Communications, 2021 Biomedical measurements usually generate high-dimensional data where individual samples are classified in several categories. Vogelstein et al. propose a supervised dimensionality reduction method which estimates the low-dimensional data projection for ...
Joshua T. Vogelstein +6 more
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Haisu: Hierarchically supervised nonlinear dimensionality reduction.
PLoS Computational Biology, 2022 We propose a novel strategy for incorporating hierarchical supervised label information into nonlinear dimensionality reduction techniques. Specifically, we extend t-SNE, UMAP, and PHATE to include known or predicted class labels and demonstrate the ...
Kevin Christopher VanHorn +1 more
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On the dimensional reduction procedure [PDF]
Nuclear Physics B, 2001 15 pages, Latex, enlarged discussion added in Sec 3 and typos corrected. Version to appear in Nucl.
Cognola, Guido, Zerbini, Sergio
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2D Dimensionality Reduction Methods without Loss [PDF]
Journal of Artificial Intelligence and Data Mining, 2019 In this paper, several two-dimensional extensions of principal component analysis (PCA) and linear discriminant analysis (LDA) techniques has been applied in a lossless dimensionality reduction framework, for face recognition application.
S. Ahmadkhani, P. Adibi, A. ahmadkhani
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Dimensionality reduction methods [PDF]
Advances in Methodology and Statistics, 2005 In case one or more sets of variables are available, the use of dimensional reduction methods could be necessary. In this contest, after a review on the link between the Shrinkage Regression Methods and Dimensional Reduction Methods, authors provide a different multivariate extension of the Garthwaite's PLS approach (1994) where a simple linear ...
D'AMBRA L, AMENTA P, GALLO, Michele
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Evaluating dimensionality reduction for genomic prediction
Frontiers in Genetics, 2022 The development of genomic selection (GS) methods has allowed plant breeding programs to select favorable lines using genomic data before performing field trials.
Vamsi Manthena +8 more
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