Results 21 to 30 of about 24,058,587 (288)
Stochastic Canonical Correlation Analysis
J. Mach. Learn. Res., 2017 We study the sample complexity of canonical correlation analysis (CCA), \ie, the number of samples needed to estimate the population canonical correlation and directions up to arbitrarily small error. With mild assumptions on the data distribution, we show that in order to achieve $ε$-suboptimality in a properly defined measure of alignment between the
Chao Gao +4 more
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Robust Sparse Canonical Correlation Analysis [PDF]
SSRN Electronic Journal, 2015 Canonical correlation analysis (CCA) is a multivariate statistical method which describes the associations between two sets of variables. The objective is to find linear combinations of the variables in each data set having maximal correlation. This paper discusses a method for Robust Sparse CCA.
Ines Wilms, Christophe Croux
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Kernel Generalized Canonical Correlation Analysis [PDF]
Computational Statistics & Data Analysis, 2015 There is a growing need to analyze datasets characterized by several sets of variables observed on a single set of observations. Such complex but structured dataset are known as multiblock dataset, and their analysis requires the development of new and flexible tools.
Tenenhaus, Arthur +2 more
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Kernel functional canonical correlation analysis
Acta Universitatis Lodziensis. Folia Oeconomica, 2016 Canonical correlation methods for data representing functions or curves have received much attention in recent years. Such data, known in the literature as functional data (Ramsay and Silverman, 2005), has been the subject of much recent research ...
Mirosław Krzyśko, Łukasz Waszak
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Canonical correlation analysis: an introduction to a multivariate statistical analysis
Journal of the College of Community Physicians, 2019 No abstract ...
Nuwan Darshana Wickramasinghe
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Estimating the Number of Significant Canonical Coordinates
IEEE Access, 2019 This study proposes a novel model selection criterion for dimensionality estimation in canonical correlation analysis (CCA), which can be used to estimate the number of correlated components between two sets of multivariate vectors, particularly in the ...
Abd-Krim Seghouane, Navid Shokouhi
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Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome. [PDF]
, 2010 peer-reviewedBackground Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment.
Morine Melissa J +23 more
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Classification of Crystallographic Data Using Canonical Correlation Analysis
EURASIP Journal on Advances in Signal Processing, 2007 A reliable and automatic method is applied to crystallographic data for tissue typing. The technique is based on canonical correlation analysis, a statistical method which makes use of the spectral-spatial information characterizing X-ray diffraction ...
Lamura A, Laudadio T, Ladisa M
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Multi-block Analysis of Genomic Data Using Generalized Canonical Correlation Analysis [PDF]
Genomics & Informatics, 2018 Recently, there have been many studies in medicine related to genetic analysis. Many genetic studies have been performed to find genes associated with complex diseases.
Inyoung Jun, Wooree Choi, Mira Park
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Non-Linear Canonical Correlation Analysis Using Alpha-Beta Divergence
Entropy, 2013 We propose a generalized method of the canonical correlation analysis using Alpha-Beta divergence, called AB-canonical analysis (ABCA). From observations of two random variables, x ∈ RP and y ∈ RQ, ABCA finds directions, wx ∈ RP and wy ∈ RQ, such that ...
Andrzej Cichocki, Abhijit Mandal
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