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Orthogonal Multi-view Analysis by Successive Approximations via Eigenvectors
We propose a unified framework for multi-view subspace learning to learn individual orthogonal projections for all views.
A Self-consistent-field Iteration for Orthogonal Canonical Correlation Analysis
In this paper, we propose an alternating numerical scheme whose core is the sub-maximization problem in the trace-fractional form with an orthogonal constraint.
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