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Permutation inference for canonical correlation analysis [PDF]
NeuroImage, 2020 Canonical correlation analysis (CCA) has become a key tool for population neuroimaging, allowing investigation of associations between many imaging and non-imaging measurements.
Anderson M. Winkler +3 more
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Longitudinal Canonical Correlation Analysis. [PDF]
J R Stat Soc Ser C Appl Stat, 2023 AbstractThis paper considers canonical correlation analysis for two longitudinal variables that are possibly sampled at different time resolutions with irregular grids. We modelled trajectories of the multivariate variables using random effects and found the most correlated sets of linear combinations in the latent space.
Lee S +4 more
europepmc +5 more sources
Fair Canonical Correlation Analysis. [PDF]
Adv Neural Inf Process Syst, 2023 Accepted for publication at NeurIPS 2023, 31 Pages, 14 ...
Zhou Z +7 more
europepmc +4 more sources
An Improved Canonical Correlation Analysis for EEG Inter-Band Correlation Extraction [PDF]
Bioengineering, 2023 (1) Background: Emotion recognition based on EEG signals is a rapidly growing and promising research field in affective computing. However, traditional methods have focused on single-channel features that reflect time-domain or frequency-domain ...
Zishan Wang +8 more
doaj +2 more sources
Multimodal Brain Growth Patterns: Insights from Canonical Correlation Analysis and Deep Canonical Correlation Analysis with Auto-Encoder [PDF]
InformationToday’s advancements in neuroimaging have been pivotal in enhancing our understanding of brain development and function using various MRI techniques.
Ram Sapkota +4 more
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Robust Sparse Canonical Correlation Analysis [PDF]
SSRN Electronic Journal, 2014 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.
Croux, Christophe, Wilms, Ines
core +6 more sources
Structure-adaptive canonical correlation analysis for microbiome multi-omics data [PDF]
Frontiers in GeneticsSparse canonical correlation analysis (sCCA) has been a useful approach for integrating different high-dimensional datasets by finding a subset of correlated features that explain the most correlation in the data.
Linsui Deng +3 more
doaj +2 more sources
Chunk Incremental Canonical Correlation Analysis [PDF]
Jisuanji kexue yu tansuo, 2022 For the large-scale dynamic data stream, incremental learning is an effective and efficient technique and is widely used in machine learning. Incremental dimensionality reduction algorithms have been proposed by many scholars.
PAN Yu, CHEN Xiaohong, LI Shunming, LI Jiyong
doaj +1 more source
Canonical Concordance Correlation Analysis
Mathematics, 2022 A multivariate technique named Canonical Concordance Correlation Analysis (CCCA) is introduced. In contrast to the classical Canonical Correlation Analysis (CCA) which is based on maximization of the Pearson’s correlation coefficient between the linear ...
Stan Lipovetsky
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The relationship between teachers' attitudes towards distance education and their digital literacy levels [PDF]
Journal of Pedagogical Research, 2023 The purpose of this study was to examine the relationship between teachers' attitudes towards distance education and their digital literacy levels. Teachers' attitudes towards distance education and digital literacy levels were determined using a survey ...
Selda Uzun +3 more
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