Results 21 to 30 of about 496,805 (322)

Nonlinear Canonical Correlation Analysis:A Compressed Representation Approach

Entropy, 2020
Canonical Correlation Analysis (CCA) is a linear representation learning method that seeks maximally correlated variables in multi-view data. Nonlinear CCA extends this notion to a broader family of transformations, which are more powerful in many real ...
Amichai Painsky, Meir Feder, Naftali Tishby   +2 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, Vishal Kumar, Asif Laghari, Shakir Muhammad Shaikh, Shahid Karim   +4 more
doaj   +1 more source

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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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
openaire   +3 more sources

Nonequilibrium Evolution of Correlation Functions: A Canonical Approach [PDF]

, 2003
We study nonequilibrium evolution in a self-interacting quantum field theory invariant under space translation only by using a canonical approach based on the recently developed Liouville-von Neumann formalism.
A. Dolgov, A. Peter, A. Yates, A.J. Gill, A.K. Rajagopal, A.V. Ryzhov, B. Mihaila, B. Mihaila, C. Greiner, C. Wetterich, C. Wetterich, C. Wetterich, C.M. Bender, D. Bak, D. Boyanovsky, D. Boyanovsky, D. Boyanovsky, D. Boyanovsky, D. Boyanovsky, D. Boyanovsky, D. Boyanovsky, D. Ibaceta, D.I. Kaiser, E. Calzetta, E.J. Austin, F. C. Khanna, F. Cooper, F. Cooper, F. Cooper, F. Cooper, F. Cooper, G. Aarts, G. Aarts, G. Aarts, G. Aarts, G. Aarts, G. Karra, G.F. Bonini, G.J. Stephens, H. Kleinert, H.R. Lewis, Jr., I.A. Malkin, J. Baacke, J. Baacke, J. Baacke, J. Berges, J. Berges, J. Borrill, J. Killingbeck, J. Schwinger, J.K. Kim, J.M. Cornwall, J.M. Hauser, K. Chao, K. Mahanthappa, K. Rajagopal, K.B. Blagoev, L. Bettencourt, L. Kofman, L.M.A. Bettencourt, L.V. Keldysh, M. Gleiser, M. Salle, M. Salle, M. Salle, M. Yoshimura, N.D. Antunes, O. Eboli, P. Laguna, P.M. Bakshi, P.M. Bakshi, P.M. Stevenson, P.M. Stevenson, R. Balian, R. Ray, R.H. Kraichnan, R.H. Kraichnan, R.H. Kraichnan, R.J. Rivers, R.J. Rivers, S. Digal, S. Digal, S. Digal, S. Digal, S. Digal, S.J. Chang, S.J. Chang, S.J. Wang, S.P. Kim, S.P. Kim, S.P. Kim, S.P. Kim, S.P. Kim, S.P. Kim, S.P. Kim, S.Yu. Khlebnikov, S.Yu. Khlebnikov, Sang Pyo Kim, Supratim Sengupta, T.W.B. Kibble, V.V. Dodonov, W.E. Caswell, W.H. Zurek, W.H. Zurek, Y. Shtanov   +104 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
openaire   +4 more sources

A Jacobi–Davidson Method for Large Scale Canonical Correlation Analysis

Algorithms, 2020
In the large scale canonical correlation analysis arising from multi-view learning applications, one needs to compute canonical weight vectors corresponding to a few of largest canonical correlations.
Zhongming Teng, Xiaowei Zhang
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Sparse canonical correlation analysis [PDF]

Machine Learning, 2010
We present a novel method for solving Canonical Correlation Analysis (CCA) in a sparse convex framework using a least squares approach. The presented method focuses on the scenario when one is interested in (or limited to) a primal representation for the first view while having a dual representation for the second view.
Hardoon, David R., Shawe-Taylor, John
openaire   +3 more sources

Non‐linear canonical correlation† [PDF]

British Journal of Mathematical and Statistical Psychology, 1983
Non‐linear canonical correlation analysis is a method for canonical correlation analysis with optimal scaling features. The method fits many kinds of discrete data. The different parameters are solved for in an alternating least squares way and the corresponding program is called CANALS.
van der Burg, Eeke, de Leeuw, Jan
openaire   +1 more source

Determinant indicators for labor market efficiency and higher education and training: evidence from Middle East and North Africa countries [PDF]

Problems and Perspectives in Management, 2020
This study aims to explore the determinant indicators for the labor market efficiency and the higher education and training factors that can help in increasing the productivity in labor market and the quality in higher education and training, as well as ...
Elsayed A. H. Elamir
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