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Towards Aligned Canonical Correlation Analysis: Preliminary Formulation and Proof-of-Concept Results (2312.00296v2)
Published 1 Dec 2023 in cs.LG and stat.ML
Abstract: Canonical Correlation Analysis (CCA) has been widely applied to jointly embed multiple views of data in a maximally correlated latent space. However, the alignment between various data perspectives, which is required by traditional approaches, is unclear in many practical cases. In this work we propose a new framework Aligned Canonical Correlation Analysis (ACCA), to address this challenge by iteratively solving the alignment and multi-view embedding.