Sparse canonical correlation analysis (CCA) is a useful statistical tool to detect latent information with sparse structures. However, sparse CCA, where the sparsity could be considered as a Laplace prior on the canonical variates, works only for two data sets, that is, there are only two views or two distinct objects. To overcome this limitation, we propose a sparse generalized canonical correlation analysis (GCCA), which could detect the latent relations of multiview data with sparse structures. Specifically, we convert the GCCA into a linear system of equations and impose ℓ1 minimization penalty to pursue sparsity. This results in a nonconvex problem on the Stiefel manifold. Based on consensus optimization, a distributed alternating iteration approach is developed, and consistency is investigated elaborately under mild conditions. Experiments on several synthetic and real-world data sets demonstrate the effectiveness of the proposed algorithm.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1162/neco_a_01673 | DOI Listing |
Alzheimers Dement
December 2024
Laboratory of Clinical Investigation, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA.
Background: Cognitive decline during normative aging significantly impacts the quality of life, while the rate varies among individuals. MRI studies have highlighted the correlation between cognitive functions and brain macrostructure. However, cerebral microstructural alterations, especially in white matter, may precede macrostructural changes, driving early cognitive decline.
View Article and Find Full Text PDFBackground: Understanding the relationship between genetic variations and brain imaging phenotypes is an important issue in Alzheimer's disease (AD) research. As an alternative to GWAS univariate analyses, canonical correlation analysis (CCA) and its deep learning extension (DCCA) are widely used to identify associations between multiple genetic variants such as SNPs and multiple imaging traits such as brain ROIs from PET/MRI. However, with the recent availability of numerous genetic variants from genotyping and whole genome sequencing data for AD, these approaches often suffer from severe overfitting when dealing with 'fat' genetics data, e.
View Article and Find Full Text PDFJ Chem Phys
January 2025
Department of Chemical Engineering, University of Massachusetts Amherst, 686 North Pleasant Street, Amherst, Massachusetts 01003-9303, USA.
A comprehensive set of single-component and binary isotherms were collected for ethanol/water adsorption into the siliceous forms of 185 known zeolites using grand-canonical Monte Carlo simulations. Using these data, a systematic analysis of ideal/real adsorbed-solution theory (IAST/RAST) was conducted and activity coefficients were derived for ethanol/water mixtures adsorbed in different zeolites based on RAST. It was found that activity coefficients of ethanol are close to unity while activity coefficients of water are larger in most zeolites, indicating a positive excess free energy of the mixture.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
University of Pennsylvania, Philadelphia, PA, USA.
Background: Measures of tau burden have typically relied upon measures of magnitude, such as mean standardized uptake value ratio (SUVR), or extent, such as number of tau positive regions. However, heterogenous patterns of tau spread and accumulation present challenges to using these measures in isolation to quantify tau burden. Therefore, we hypothesized that a combined measure of tau magnitude and extent (Tau-MaX) would outperform either measure in isolation.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Laboratory of Clinical Investigation, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA.
Background: Cognitive decline during normative aging significantly impacts the quality of life, while the rate varies among individuals. MRI studies have highlighted the correlation between cognitive functions and brain macrostructure. However, cerebral microstructural alterations, especially in white matter, may precede macrostructural changes, driving early cognitive decline.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!