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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
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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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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
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Neurons as Canonical Correlation Analyzers [PDF]
Frontiers in Computational Neuroscience, 2020 Normative models of neural computation offer simplified yet lucid mathematical descriptions of murky biological phenomena. Previously, online Principal Component Analysis (PCA) was used to model a network of single-compartment neurons accounting for ...
Cengiz Pehlevan +4 more
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Fair Canonical Correlation Analysis. [PDF]
Adv Neural Inf Process Syst, 2023 Accepted for publication at NeurIPS 2023, 31 Pages, 14 ...
Zhou Z +7 more
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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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Permutation inference for canonical correlation analysis
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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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
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Exploring Breed-Specific Milk Coagulation in Spanish Dairy Sheep: A Canonical Correlation Approach [PDF]
AnimalsThe transformation of milk into cheese largely depends on the technological properties of the raw material, with breed being a crucial factor that influences both the composition and coagulation properties of the milk used for cheesemaking.
Javier Caballero-Villalobos +6 more
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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
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