Towards Aligned Canonical Correlation Analysis: Preliminary Formulation and Proof-of-Concept Results

• URL: http://arxiv.org/abs/2312.00296v2
• Date: Fri, 8 Dec 2023 01:04:36 GMT
• Title: Towards Aligned Canonical Correlation Analysis: Preliminary Formulation and Proof-of-Concept Results
• Authors: Biqian Cheng, Evangelos E. Papalexakis, Jia Chen
• Abstract summary: Canonical Correlation Analysis (CCA) has been widely applied to jointly embed multiple views of data in a maximally correlated latent space. The alignment between various data perspectives, which is required by traditional approaches, is unclear in many practical cases. We propose a new framework Aligned Canonical Correlation Analysis (ACCA), to address this challenge by iteratively solving the alignment and multi-view embedding.
• Score: 6.933535396099733
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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