Results 21 to 30 of about 9,586,369 (306)
Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model
Genome Biology, 2019 Single-cell RNA-Seq (scRNA-Seq) profiles gene expression of individual cells. Recent scRNA-Seq datasets have incorporated unique molecular identifiers (UMIs). Using negative controls, we show UMI counts follow multinomial sampling with no zero inflation.
F. W. Townes +3 more
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Local Deep-Feature Alignment for Unsupervised Dimension Reduction [PDF]
IEEE Transactions on Image Processing, 2018 This paper presents an unsupervised deep-learning framework named local deep-feature alignment (LDFA) for dimension reduction. We construct neighbourhood for each data sample and learn a local stacked contractive auto-encoder (SCAE) from the ...
Jian Zhang, Jun Yu, D. Tao
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Tensor sufficient dimension reduction [PDF]
WIREs Computational Statistics, 2015 Tensor is a multiway array. With the rapid development of science and technology in the past decades, large amount of tensor observations are routinely collected, processed, and stored in many scientific researches and commercial activities nowadays. The colorimetric sensor array (CSA) data is such an example.
Zhong, Wenxuan +2 more
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Quantile treatment effect estimation with dimension reduction
Statistical Theory and Related Fields, 2020 Quantile treatment effects can be important causal estimands in evaluation of biomedical treatments or interventions for health outcomes such as medical cost and utilisation.
Ying Zhang +3 more
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Modern Dimension Reduction [PDF]
, 2021 83 pages, 36 figures, to appear in the Cambridge University Press Elements in Quantitative and Computational Methods for the Social Sciences ...
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A Review on Dimension Reduction [PDF]
International Statistical Review, 2012 RésuméRésumer l'impact d'un nombre élevé de variables explicatives à celui d'un nombre réduit de combinaisons linéaires bien choisies constitue une façon efficace de réduire la dimension d'un problème. Cette réduction à un petit nombre de combinaisons linéaires est réalisée à partir d'hypothèses minimales sur la forme de la dépendance et jouit, par ...
Ma, Yanyuan, Zhu, Liping
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Gradient-Based Dimension Reduction of Multivariate Vector-Valued Functions [PDF]
SIAM Journal on Scientific Computing, 2018 We propose a gradient-based method for detecting and exploiting low-dimensional input parameter dependence of multivariate functions. The methodology consists in minimizing an upper bound, obtained by Poincar\'e-type inequalities, on the approximation ...
O. Zahm +3 more
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Dimension reduction with expectation of conditional difference measure
Statistical Theory and Related Fields, 2023 In this article, we introduce a flexible model-free approach to sufficient dimension reduction analysis using the expectation of conditional difference measure.
Wenhui Sheng, Qingcong Yuan
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, 2021 When data objects that are the subject of analysis using machine learning techniques are described by a large number of features (i.e. the data is high dimension) it is often beneficial to reduce the dimension of the data. Dimension reduction can be beneficial not only for reasons of computational efficiency but also because it can improve the accuracy
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Principal Fitted Components for Dimension Reduction in Regression [PDF]
, 2008 We provide a remedy for two concerns that have dogged the use of principal components in regression: (i) principal components are computed from the predictors alone and do not make apparent use of the response, and (ii) principal components are not ...
Cook, R. Dennis, Forzani, Liliana
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