Dimensional Reduction of Nonlinear Gauge Theories [PDF]
Journal of High Energy Physics, 2004 20 pages, crucial references ...
Noriaki Ikeda, K. I. Izawa
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Artifacts in Simultaneous hdEEG/fMRI Imaging: A Nonlinear Dimensionality Reduction Approach [PDF]
Sensors, 2019 Simultaneous recordings of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) are at the forefront of technologies of interest to physicians and scientists because they combine the benefits of both modalities—better time ...
Marek Piorecky +4 more
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A tied-weight autoencoder for the linear dimensionality reduction of sample data [PDF]
Scientific ReportsDimensionality reduction is a method used in machine learning and data science to reduce the dimensions in a dataset. While linear methods are generally less effective at dimensionality reduction than nonlinear methods, they can provide a linear ...
Sunhee Kim +3 more
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Nonlinear dimensionality reduction based visualization of single-cell RNA sequencing data [PDF]
Journal of Analytical Science and TechnologySingle-cell multi-omics technology has catalyzed a transformative shift in contemporary cell biology, illuminating the nuanced relationship between genotype and phenotype.
Mohamed Yousuff +2 more
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Nonlinear Dimensionality Reduction Based on HSIC Maximization
IEEE Access, 2018 Hilbert-Schmidt independence criterion (HSIC) is typically used to measure the statistical dependence between two sets of data. HSIC first transforms these two sets of data into two reproducing Kernel Hilbert spaces (RKHS), respectively, and then ...
Zhengming Ma +3 more
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Application of Linear and Nonlinear Dimensionality Reduction Methods [PDF]
, 2012 This work was supported by the NSF grant CMMI-0953449, NIDRR grant H133F100001. Special thanks to Laurens van der Maaten for guidance with the dimensionality reduction toolbox, and Prof. Dan Ventura (Brigham Young University) for helpful notes on comparison of LLE and Isomap. Thanks to Stephen Foldes for his suggestions with formatting.
Mingui Sun +3 more
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Reduction of dimensionality in dynamic programming-based solution methods for nonlinear integer programming [PDF]
International Journal of Mathematics and Mathematical Sciences, 1988 This paper suggests a method of formulating any nonlinear integer programming problem, with any number of constraints, as an equivalent single constraint problem, thus reducing the dimensionality of the associated dynamic programming problem.
Balasubramanian Ram, A. J. G. Babu
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Forward Stepwise Deep Autoencoder-Based Monotone Nonlinear Dimensionality Reduction Methods [PDF]
J Comput Graph Stat, 2020 Youyi Fong, Jun Xu
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Dimensionality reduction on quadratic manifolds augments linear approximations with quadratic correction terms. Previous works rely on linear approximations given by projections onto the first few leading principal components of the training data; however, linear approximations in subspaces spanned by the leading principal components alone can miss ...
Schwerdtner, Paul +1 more
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Letter to the Editor Regarding Paper “Automatic Computation of Left Ventricular Volume Changes over a Cardiac Cycle from Echocardiography Images by Nonlinear Dimensionality Reduction” [PDF]
J Digit Imaging, 2014 Saeed Ranjbar, Mersedeh Karvandi
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