Results 141 to 150 of about 274,693 (175)

Generalized Canonical Correlation Analysis: A Subspace Intersection Approach [PDF]

IEEE Transactions on Signal Processing, 2021
Generalized Canonical Correlation Analysis (GCCA) is an important tool that finds numerous applications in data mining, machine learning, and artificial intelligence. It aims at finding `common' random variables that are strongly correlated across multiple feature representations (views) of the same set of entities. CCA and to a lesser extent GCCA have
Charilaos I Kanatsoulis, Nicholas D Sidiropoulos, Mikael Sorensen   +2 more
exaly   +5 more sources

A Perturbation Bound on the Subspace Estimator from Canonical Projections

2022 IEEE International Symposium on Information Theory (ISIT), 2022
To appear in Proc.
Daniel L Pimentel-Alarcón
exaly   +3 more sources

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A Canonical CS Representation of a Pair of Subspaces

SIAM Journal on Matrix Analysis and Applications, 2016
Summary: Let \({\mathcal X}\) and \({\mathcal Y}\) be subspaces of \(\mathbb{R}^{n}\) of dimensions \(k\) and \(l\) with \(k\leq l\). Let \(X\) and \(Y\) be orthonormal bases for \({\mathcal X}\) and \({\mathcal Y}\). This paper describes canonical forms for \(X\) and \(Y\) under orthogonal transformations.
G W Stewart
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Approximate Canonical Correlation Analysis for common/specific subspace decompositions [PDF]

Biomedical Signal Processing and Control, 2021
The objective of this paper is to present a new technique for jointly decomposing two sets of signals. The proposed method is a modified version of Canonical Correlation Analysis (CCA), which automatically identifies from the two (a priori noisy) data-sets, having the same number of samples but potentially different number of variables (measurements ...
Radu Ranta, Louis Maillard, Sophie Colnat-Coulbois   +2 more
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Canonical analysis relative to a closed subspace

Linear Algebra and Its Applications, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dauxois, J, Nkiet, G.M, Romain, Y
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The distance between feature subspaces of kernel canonical correlation analysis

Mathematical and Computer Modelling, 2013
Abstract Kernel canonical correlation analysis (CCA) is a nonlinear extension of CCA. It is widely used in information retrieval. However, relatively little research concerning the convergence rate and the distance between two feature spaces has been done so far.
Jia Cai
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Sharp Kernels and Canonical Subspaces (Revised)

American Journal of Mathematics, 1988
The author studies certain invariant subspaces under the m-tuple of multiplication by the coordinate functions on an analytic functional Hilbert space over a bounded domain of C m, \(m>I\).
Agrawal, Om P., Salinas, Norberto
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Efficient Bounds and Estimates for Canonical Angles in Randomized Subspace Approximations

SIAM Journal on Matrix Analysis and Applications
Accepted at SIAM Journal on Matrix Analysis and ...
Yuji Nakatsukasa, Gunnar Martinsson
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Randomized Subspace Iteration: Analysis of Canonical Angles and Unitarily Invariant Norms

SIAM Journal on Matrix Analysis and Applications, 2019
25 pages, 4 figures.
Arvind K Saibaba
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Rotated canonical analysis onto a reference subspace

Computational Statistics & Data Analysis, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
BALBI, SIMONA, ESPOSITO VINZI, VINCENZO
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