mlsanityData to 7 Oct 2026

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

arXiv 2312.00296 ↗First posted 1 Dec 2023cs.LG stat.MLcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 5 of its 11 references that are in the map. First posted on arXiv 1 Dec 2023.

Builds on

5 of 11 references.

References · 5

  1. 2021Barlow Twins: Self-Supervised Learning via Redundancy Reductioncited by 1,818
  2. 2023A Cookbook of Self-Supervised Learningcited by 248
  3. 2021From Canonical Correlation Analysis to Self-supervised Graph Neural Networkscited by 138
  4. 2021Graph Barlow Twins: A self-supervised representation learning framework for graphscited by 85
  5. 2018Graph Multiview Canonical Correlation Analysiscited by 10

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Unpaired Canonical Correlation Analysiscited by 0