Towards Aligned Canonical Correlation Analysis: Preliminary Formulation and Proof-of-Concept Results
Biqian Cheng, Evangelos E. Papalexakis, Jia Chen
12/1/2023
cs.LGstat.ML
No confident code implementation found for this paper.
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.
