Results 11 to 20 of about 183,993 (251)
Supervised Canonical Correlation Analysis Based on Deep Learning [PDF]
Jisuanji gongcheng, 2022 Canonical Correlation Analysis (CCA) is a multivariate statistical method, which uses the correlation between comprehensive variable pairs to reflect the overall correlation between two groups of indicators.The traditional CCA method can not effectively ...
ZHANG Heng, CHEN Xiaohong, LAN Yuxiang, LI Shunming
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Sufficient Canonical Correlation Analysis [PDF]
IEEE Transactions on Image Processing, 2016 Canonical correlation analysis (CCA) is an effective way to find two appropriate subspaces in which Pearson's correlation coefficients are maximized between projected random vectors. Due to its well-established theoretical support and relatively efficient computation, CCA is widely used as a joint dimension reduction tool and has been successfully ...
Guo, Y, Ding, X, Liu, C, Xue, J-H
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Incremental Canonical Correlation Analysis
Applied Sciences, 2020 Canonical correlation analysis (CCA) is a kind of a simple yet effective multiview feature learning technique. In general, it learns separate subspaces for two views by maximizing their correlations.
Hongmin Zhao, Dongting Sun, Zhigang Luo
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Canonical Correlation Analysis to Biomass CHONS Prediction
Chemical Engineering Transactions, 2023 Fermentation biomasses can be defined as a complex mixture of different natural components and microbes, having biodegradable and organic waste as the primary source. Its correct characterization is crucial to have proper processing in fermentative units.
Federico Moretta +4 more
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Tensor canonical correlation analysis [PDF]
Stat, 2019 Canonical correlation analysis (CCA) is a multivariate analysis technique for estimating a linear relationship between two sets of measurements. Modern acquisition technologies, for example, those arising in neuroimaging and remote sensing, produce data in the form of multidimensional arrays or tensors.
Eun Jeong Min, Eric C. Chi, Hua Zhou
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Measuring entrepreneurship determinants: empirical analysis
Agricultural and Resource Economics, 2021 Purpose. The aim of this article is to assess the main determinants that affect entrepreneurial activity, and also the mechanism of its regulation in five countries (Ukraine, Romania, Lithuania, Poland, Germany) during the period from 2007 to 2018 ...
Viktoriia Kyfyak +3 more
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Effect of Soil Aeration and Root Morphology on Yield under Aerated Irrigation
Agronomy, 2023 Soil compaction easily causes root hypoxia stress, resulting in poor root growth and the absorption of soil water and nutrients. We hypothesized that aerated irrigation (AI) could enhance nutrient uptake and utilization, thus unlocking the high yield ...
Cuicui Jin +6 more
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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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Process Monitoring Using Canonical Correlation Analysis
JISR on Computing, 2019 Principal component analysis (PCA) and partial least square (PLS) used for fault diagnosis and process monitoring for systems. It is expected that the information to be examined isn't self-connected.
Yin SHEN +4 more
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Ensemble canonical correlation analysis
Applied Intelligence, 2013 Canonical Correlation Analysis (CCA) aims at identifying linear dependencies between two different but related multivariate views of the same underlying semantics. Ignoring its various extensions to more than two views, CCA uses these two views as complex labels to guide the search of maximally correlated projection vectors (covariates). Therefore, CCA
Cemal Okan Sakar +2 more
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