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Canonical Correlation Analysis (CCA) is a linear representation learning method that seeks maximally correlated variables in multi-view data.
Relations between two sets of variates
Hotelling, H · 1936
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The population frequencies of species and the estimation of population parameters
Good, I.J · 1953
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The structure of bivariate distributions
Lancaster, H · 1958
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The general theory of canonical correlation and its relation to functional analysis
Hannan, E · 1961
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Information transmission with additional noise
Dobrushin, R.; Tsybakov, B · 1962
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Transmission of noisy information to a noisy receiver with minimum distortion
Wolf, J.; Ziv, J · 1970
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Modeling by shortest data description
Rissanen, J · 1978
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Non-linear canonical correlation
Van Der Burg, E.; de Leeuw, J · 1983
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Estimating optimal transformations for multiple regression and correlation
Breiman, L.; Friedman, J.H · 1985
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On universal quantization
Ziv, J · 1985
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Interpreting canonical correlation analysis through biplots of structure correlations and weights
Ter Braak, C.J · 1990
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Nonlinear multivariate analysis
Gifi, A · 1990
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On universal quantization by randomized uniform/lattice quantizers
Zamir, R.; Feder, M · 1992
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OVERALS: Nonlinear canonical correlation with k sets of variables
Van der Burg, E.; de Leeuw, J.; Dijksterhuis, G · 1994
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Information rates of pre/post-filtered dithered quantizers
Zamir, R.; Feder, M · 1996
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Empirical quantizer design in the presence of source noise or channel noise
Linder, T.; Lugosi, G.; Zeger, K · 1997
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The information bottleneck method
Tishby, N.; Pereira, F.C.; Bialek, W · 1999
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Kernel and nonlinear canonical correlation analysis
Lai, P.L.; Fyfe, C · 2000
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Facesync: A linear operator for measuring synchronization of video facial images and audio tracks
Slaney, M.; Covell, M · 2001
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A Kernel Method For Canonical Correlation Analysis
Akaho, S · 2001
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A generalized representer theorem
Schölkopf, B.; Herbrich, R.; Smola, A.J · 2001
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Kernel independent component analysis
Bach, F.R.; Jordan, M.I · 2002
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Optimal Manifold Representation of Data: An Information Theoretic Approach
Chigirev, D.V.; Bialek, W · 2003
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Estimation of entropy and mutual information
Paninski, L · 2003
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Canonical correlation analysis: An overview with application to learning methods
Hardoon, D.R.; Szedmak, S.; Shawe-Taylor, J · 2004
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Enriched biplots for canonical correlation analysis
Graffelman, J · 2005
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Bayesian canonical correlation analysis
Klami, A.; Virtanen, S.; Kaski, S · 2013
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Deep canonical correlation analysis
Andrew, G.; Arora, R.; Bilmes, J.A.; Livescu, K · 2013
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Qualitative activity recognition of weight lifting exercises
Velloso, E.; Bulling, A.; Gellersen, H.; Ugulino, W.; Fuks, H · 2013
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Improving image-sentence embeddings using large weakly annotated photo collections
Gong, Y.; Wang, L.; Hodosh, M.; Hockenmaier, J.; Lazebnik, S · 2014
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Lattice Coding for Signals and Networks: A Structured Coding Approach to Quantization, Modulation, and Multiuser Information Theory
Zamir, R · 2014
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On Deep Multi-View Representation Learning
Wang, W.; Arora, R.; Livescu, K.; Bilmes, J.A · 2015
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Chechik, G.; Globerson, A.; Tishby, N.; Weiss, Y · 2005
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A distribution-free theory of nonparametric regression
Györfi, L.; Kohler, M.; Krzyzak, A.; Walk, H · 2006
Cited alongside, same era.
Multivariate information bottleneck
Slonim, N.; Friedman, N.; Tishby, N · 2006
Cited alongside, same era.
Tensor canonical correlation analysis for action classification
Kim, T.K.; Wong, S.F.; Cipolla, R · 2007
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Variational Bayesian approach to canonical correlation analysis
Wang, C · 2007
Cited alongside, same era.
Quantization for nonparametric regression
Györfi, L.; Wegkamp, M · 2008
Cited alongside, same era.
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Stochastic optimization for deep CCA via nonlinear orthogonal iterations
Wang, W.; Arora, R.; Livescu, K.; Srebro, N · 2015
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An efficient algorithm for information decomposition and extraction
Makur, A.; Kozynski, F.; Huang, S.L.; Zheng, L · 2015
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Competitive distribution estimation: Why is good-turing good
Orlitsky, A.; Suresh, A.T · 2015
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Nonparametric canonical correlation analysis
Michaeli, T.; Wang, W.; Livescu, K · 2016
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Stochastic optimization for multiview representation learning using partial least squares
Arora, R.; Mianjy, P.; Marinov, T · 2016
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On deep multi-view representation learning: objectives and optimization
Wang, W.; Arora, R.; Livescu, K.; Bilmes, J · 2016
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Stochastic Approximation for Canonical Correlation Analysis
Arora, R.; Marinov, T.V.; Mianjy, P.; Srebro, N · 2017
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Exploration of geochemical data with compositional canonical biplots
Graffelman, J.; Pawlowsky-Glahn, V.; Egozcue, J.J.; Buccianti, A · 2018
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The Role of the Information Bottleneck in Representation Learning
Vera, M.; Piantanida, P.; Vega, L.R · 2018
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On the universality of the logistic loss function
Painsky, A.; Wornell, G · 2018
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Large-Scale Sparse Kernel Canonical Correlation Analysis
Uurtio, V.; Bhadra, S.; Rousu, J · 2019
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Accelerated Kernel Canonical Correlation Analysis with Fault Relevance for Nonlinear Process Fault Isolation
Yu, J.; Wang, K.; Ye, L.; Song, Z · 2019
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Bregman Divergence Bounds and Universality Properties of the Logarithmic Loss
Painsky, A.; Wornell, G.W · 2019
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